GITNUXSOFTWARE REVIEW
Science ResearchTop 10 Best Moon Stacking Software of 2026
Compare moon stacking software options for stacking workflows, tool features, and practical tradeoffs for imaging teams.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
Agents extract product evidence with provenance, then collect written reviews and transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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PixInsight is the best pick for technical lunar imagers who need deterministic, repeatable pipelines because its process-to-process JavaScript scripting and batchable parameter control keep calibration, alignment, rejection, and stacking consistent across sessions, while Siril fits open-source teams that want a FITS-centric workflow with integrated quality-threshold frame rejection and alignment feedback.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
PixInsight
Process-to-process scripting and batchable parameter control through JavaScript across alignment, rejection, and stacking stages.
Best for: Fits when technical imagers need deterministic, repeatable calibration and stacking pipelines across many sessions.
Siril
Editor pickQuality-threshold frame rejection with alignment feedback before stack generation and export.
Best for: Fits when teams need repeatable FITS-based calibration and frame alignment with scriptable batch workflows.
SharpCap
Editor pickFWHM sorting tied to live capture review, enabling frame rejection decisions during the run.
Best for: Fits when visual quality gating and interactive capture tuning matter more than heavy automation.
Comparison Table
PixInsight
specialistDeep sky and lunar image processing platform with advanced alignment, stacking, and calibration modules.
Process-to-process scripting and batchable parameter control through JavaScript across alignment, rejection, and stacking stages.
PixInsight is a desktop moon-stacking system built around repeatable calibration, alignment, and stacking workflows for FITS-based astrophotography. It supports frame alignment with multiple point strategies, quality-driven rejection, and stacking combinations that preserve fine gradients for deep-later output.
Its strength is extensibility via JavaScript scripting, built-in process chaining, and project-based repeatability that reduces manual rework across sessions. For teams and serious imagers, automation hinges on scriptable parameters and deterministic pipeline ordering rather than a separate capture pipeline.
- +Project-based, process-chain workflows keep calibration and alignment repeatable
- +Quality-guided alignment and rejection reduce bad-frame contamination
- +Extensible automation via JavaScript scripting for batch parameter control
- +Strong output control for FITS containers and later export stages
- –Steep learning curve for process ordering and parameter tuning
- –No integrated capture stack and alignment runtime for live stacking
- –Automation is script-driven and not a turnkey web-style pipeline
- –Batch runs can require careful memory planning on large stacks
Deep-sky astrophotographers
Stack imperfect nights with quality rejection
Cleaner integrated deep-sky stack
Astrophotography educators
Teach repeatable calibration and stacking
More consistent learning results
Show 2 more scenarios
Moon and planet imagers
Create focus-optimized stacks from planes
Controlled focus-plane composite
Aligns frames from different focus planes and combines them to control focus across the final output.
Deep-sky imaging teams
Integrate calibrated frames across nights
Single integrated image
Calibrates, registers, and combines light frames from multiple sessions into one consistent result.
Best for: Fits when technical imagers need deterministic, repeatable calibration and stacking pipelines across many sessions.
Siril
vertical specialistOpen-source astronomical image processing tool with sequence stacking and registration for lunar and deep sky images.
Quality-threshold frame rejection with alignment feedback before stack generation and export.
Siril is a moon-stacking tool focused on turning raw captures into alignment-ready stacks with practical calibration and registration steps. It supports end-to-end workflows that include dark frame subtraction, flat calibration, and frame alignment before stacking into exportable image formats.
Its workflow also includes quality-based frame rejection and common post-processing steps that fit typical lucky imaging and frame alignment pipelines. Siril’s differentiation is its built-in pipeline orchestration around FITS handling and intermediate products that remain inspectable across each processing stage.
- +FITS-centric workflow keeps calibration outputs consistent across stages
- +Integrated quality thresholding for frame selection during stacking
- +Automation via scripting lets the same processing pipeline run repeatedly
- +Export outputs that match common downstream inspection and compositing steps
- –Batch processing requires scripts or careful UI sequencing for multi-target sets
- –Alignment tuning can be time-consuming when capture conditions vary widely
- –Advanced correction chains can create deep intermediate state users must track
- –Workflow coverage depends on the expected input formats and camera settings
Planetary imagers
Align and reject planetary frames
Sharper planetary image
Deep-sky astrophotographers
Stack calibrated exposures into one signal
Higher-signal integration
Show 2 more scenarios
Milky Way photographers
Register wide-field night skies
Repeatable wide-field stack
Calibrates and registers wide-field frames and stacks them into a consistent night-sky result.
Star trail photographers
Create star trails from sequences
Continuous star-trail composition
Calibrates, aligns, and stacks sequential exposures to produce a continuous star-trail image.
Best for: Fits when teams need repeatable FITS-based calibration and frame alignment with scriptable batch workflows.
SharpCap
vertical specialistAstronomy imaging application with live stacking support for lunar and planetary targets.
FWHM sorting tied to live capture review, enabling frame rejection decisions during the run.
SharpCap targets moon stacking with an end-to-end capture and processing workflow built around lucky imaging and interactive quality control. It supports frame capture to FITS and direct export pipelines that fit typical stacking work, including flat calibration and dark frame subtraction paths.
Alignment and rejection are driven through onscreen metrics like FWHM sorting and quality thresholds, then followed by stack generation and sharpen-ready output. SharpCap also includes live guidance for histogram stretching and exposure tuning so capture settings can be refined before stacking.
- +FWHM sorting and quality thresholds for fast frame rejection decisions
- +Interactive capture tools that tune exposure and histogram stretching before stacking
- +Flat calibration and dark frame subtraction are integrated into the workflow
- +Exports from capture pipelines into FITS-friendly processing paths
- –Automation across long capture sessions is limited compared with script-first stacks
- –Multipoint alignment control is less granular than specialized stacking pipelines
- –Advanced SER-style ingestion workflows depend on external handling
- –Batch quality map reporting for governance-style auditing is not the focus
Deep-sky astrophotographers
Live stack during an observing session
Progressively improved stack
Star trail photographers
Automate RAW sequence capture
Consistent sequence inputs
Show 2 more scenarios
Astrophotography teams
Hand off FITS and frame sequences
Processing-ready export files
Exports FITS, TIFF, or frame sequences for advanced downstream editing, mosaics, or stacking.
Observing teams
Validate field with star detection
Verified star-field identification
Analyzes live captures with plate solving and star detection to confirm pointing and the observed field.
Best for: Fits when visual quality gating and interactive capture tuning matter more than heavy automation.
AutoStakkert!
vertical specialistPlanetary and lunar stacking software for aligning and combining video frames into sharp images.
Registration-quality maps drive automated frame ranking and rejection before stacking, reducing alignment guesswork.
AutoStakkert! is built around detecting sharpness in captured frames and then using that signal to drive frame alignment and frame rejection. The workflow typically centers on selecting the capture input format, setting alignment point density, and choosing stack depth via quality cutoffs. Output is oriented toward feeding subsequent processing steps like wavelet sharpening or contrast balancing with consistent FITS or TIFF products.
- +Quality-threshold driven frame rejection reduces manual inspection work
- +Multi-point alignment supports nonuniform motion across the lunar disk
- +Batch-friendly processing handles SER and AVI style capture sets
- +Consistent stack outputs integrate with later wavelet sharpening tools
- –Alignment results can degrade when capture has strong drift
- –Parameter tuning requires iteration to match different seeing conditions
- –Does not replace preprocessing tools like PIPP for some SER cleanup tasks
- –Output tuning can be slower when exploring many stack depth targets
Lunar imaging hobbyists
Turn a long AVI into stacks
Cleaner stacks with less manual effort
Observatory laptop operators
Batch process nights of captures
Faster per-night production
Show 2 more scenarios
Astrophotography workflow maintainers
Feed consistent FITS outputs downstream
Less reformatting between tools
It exports stacks in a form that pairs with sharpening and histogram workflows.
High-throughput capture teams
Compare multiple alignment settings quickly
Better match to optics and sampling
It supports rerunning different alignment point densities to match target seeing and scale.
Best for: Fits when imaging teams need automated quality ranking and multi-point alignment for repeatable lunar stacks.
AstroSurface
vertical specialistPlanetary and lunar image processing software for stacking and sharpening astronomy video frames.
Derotation integrated into the alignment and stacking workflow for lunar sequences with noticeable rotation.
AstroSurface focuses on processing and stacking lunar imaging data with interactive registration and per-frame quality decisions. The workflow supports derotation and alignment-driven stacking, then exports stacked results in common imaging outputs such as TIFF and SER.
- +Interactive registration with adjustable alignment behavior for lunar sequences
- +Derotation support helps stabilize face-on lunar motion before stacking
- +Quality-based frame handling reduces blur-heavy frames in the stack
- +Exports practical outputs such as TIFF and SER for downstream tools
- –Limited automation surface compared with tools that expose stacking pipelines via scripting
- –Batch workflows depend on saved project states rather than parameterized runs
- –Fewer built-in hooks for custom rejection logic than script-driven stacks
- –Advanced pipelines can require manual tuning across sessions
Lunar imagers
Stack lunar frames with sharpening
Detailed lunar stack
Planetary astrophotographers
Stack many short planetary exposures
Cleaner stacked planetary image
Show 2 more scenarios
Solar imagers
Integrate and refine solar frames
Combined solar image
Processes and stacks solar astrophotography frames through alignment and integration steps.
Repeat imaging observers
Reuse calibration and stacking steps
More consistent outputs
Applies repeatable calibration, stacking, and export steps to frames collected during different sessions.
Best for: Fits when teams need GUI-driven lunar alignment control with repeatable projects for consistent stacks.
StarTools
SMBAstronomical image-processing software with stacking and processing workflows for captured data.
Quality-gated frame selection with session-consistent alignment and sharpening stages, so stack results stay reproducible across runs.
StarTools is a moon stacking workflow tool built around processing chains for lucky imaging, alignment, and output generation. The core value is deterministic frame handling with clear rejection controls, then consistent alignment and sharpening choices across a session.
- +Frame rejection controls support quality thresholds and consistent stack outcomes
- +FITS ingest and standard export formats fit common astronomy capture pipelines
- +Deterministic processing chain helps reproduce alignment and sharpening decisions
- +Multipoint alignment options support higher alignment point density on varied targets
- –Workflow depth increases setup time for new operators
- –Advanced alignment and calibration steps require careful parameter tuning
- –Large stacks can stress throughput on slower storage and CPUs
- –SER and AVI capture preprocessing coverage depends on the selected pipeline
Astrophotography teams
Run consistent batch alignment decisions
Fewer repeated tuning cycles
Milky Way photographers
Reduce star bloat in stacks
Cleaner Milky Way stack
Show 2 more scenarios
Lunar and lucky-imaging enthusiasts
Process lunar frames with repeatable settings
Reproducible lunar stack
Selects, aligns, rejects, and sharpens lunar frames using repeatable processing configurations.
Processing workflow learners
Experiment safely with undo and modules
More controlled refinements
Allows iterative processing changes with undo so workflow refinement can occur without committing every step.
Best for: Fits when teams need repeatable lunar stacking workflows with controlled frame rejection and export into FITS or TIFF.
RegiStax
vertical specialistImage alignment and stacking tool with wavelet processing for lunar and planetary astrophotography.
Multi-layer wavelet sharpening after stacking provides controllable deconvolution distinct from pure frame alignment tools.
RegiStax’s core loop starts with frame alignment and registration-quality evaluation, then filters frames before combining them into a final stack. The wavelet sharpening stage runs after stacking and supports multi-layer controls that target different spatial frequencies for lunar surface detail. The UI provides interactive selection of alignment reference points and allows adjusting alignment point density to manage tradeoffs between stability and micro-detail. File handling covers typical workflows by reading SER and FITS inputs and saving stack outputs in standard image formats.
- +Wavelet sharpening uses layered controls for lunar contrast at multiple spatial scales
- +Frame alignment includes interactive reference point selection with quality-guided rejection
- +Supports SER and FITS ingestion for common capture pipelines
- +Exports standard image outputs that plug into mosaic or archiving steps
- –Batch orchestration across many sessions is limited compared with pipeline-first tools
- –Alignment results can be sensitive to reference point choices
- –Advanced automation requires manual intervention rather than headless configuration
Lunar imagers
Turn raw SER into sharp stacks
Sharper lunar surface detail
Small observing teams
Iterate on frame rejection thresholds
More consistent final stacks
Show 1 more scenario
Astrophotography workflows
Integrate stacks into mosaics
Faster mosaic assembly
Standard image exports make it easy to feed stacked frames into stitching or manual retouch steps.
Best for: Fits when teams need interactive alignment tuning plus wavelet sharpening for lunar stacks.
Radix
vertical specialistPhoto product personalization software used by print commerce vendors to build custom poster editors, including astrology and moon phase compositions.
Preset-driven batch orchestration that keeps calibration, alignment, gating, and export settings synchronized per run.
Radix implements moon stacking workflows by combining frame ingestion with automated alignment and quality gating through its configurable processing pipeline. Its distinct capability is orchestration for batch runs with reusable presets that persist capture, calibration, registration, and export settings.
- +Reusable processing presets make batch runs consistent across nights
- +Configurable rejection rules reduce low-quality frame contamination
- +Export options support analysis review instead of only final composites
- +Higher-throughput batch execution suits large capture sessions
- –Some advanced alignment controls need careful calibration discipline
- –Workflow depth depends on assembling the full pipeline manually
- –Feature coverage around niche astro formats may require preprocessing
- –Debugging mis-registration relies on reading per-stage outputs
Software modernization teams
Refactor a legacy app in stages
Staged modernization path
E-commerce product teams
Extend checkout and cart rules
Cart aligned to business needs
Show 2 more scenarios
.NET platform teams
Deliver an ASP.NET business application
Maintainable feature layers
Builds integrated .NET features across APIs, interfaces, data access, and application middleware.
PHP engineering teams
Develop a PHP business platform
Maintainable PHP API
Builds server-rendered MVC apps or headless PHP backends with API contracts and regression coverage.
Best for: Fits when teams need repeatable frame alignment and quality-threshold automation across many capture batches.
Mediaclip Designer
vertical specialistWeb-to-print personalization software that supports photo products including moon phase and stacked moon poster designs through customizable templates.
Template-driven publishing of curated stack results with organized assets and reusable layouts.
Mediaclip Designer is a web-based media authoring tool that focuses on guided visual layout and publication workflows, not an astrophotography pipeline. Core capabilities center on assembling pages, managing assets, and producing output through template-driven rendering.
- +Template-based page publishing for consistent stack result presentation
- +Asset management supports repeatable delivery of TIFF or PNG outputs
- +Browser-based authoring reduces setup time for review workflows
- +Works well as a front-end for sharing alignment and rejection notes
- –No native frame alignment, quality thresholding, or stacking engine
- –Limited integration depth for automated ingest into external pipelines
- –No documented API surface for provisioning or programmatic batch runs
- –Governance controls like RBAC and audit logs are not a core fit
Astro content teams
Publish curated moon stack galleries
Faster gallery publishing workflow
Amateur astrophotographers
Organize capture sets and annotations
Less manual organization
Show 2 more scenarios
Observation group moderators
Standardize result reports across members
Consistent team deliverables
Enforce uniform page structure for sessions, equipment details, and published stack outcomes.
Media producers
Manage assets for final moon stack releases
Reusable publication layouts
Centralize images and layout components into repeatable render templates for predictable output.
Best for: Fits when teams need a repeatable publishing workspace for moon-stack deliverables, not the stacking computation itself.
Stackistry
vertical specialistOpen-source lucky imaging stacker for aligning and combining planetary and lunar video frames.
Registration-quality based frame rejection integrated into batch stacking pipelines, reducing manual curation across large datasets.
Stackistry is built around a capture-to-stack pipeline that takes image sequences and produces a stacked output with controlled acceptance criteria, including registration-quality based frame rejection. It also supports preprocessing stages such as calibration handling and optional sharpening, then applies alignment across a configurable set of reference points to improve handling of field rotation and target drift. Batch execution and repeatable configuration make it practical for frequent sessions where the same pipeline must run across many folders of SER-like or image sequences.
- +Configurable frame rejection driven by registration quality measures
- +Batch pipeline supports deterministic preprocessing to stacking outputs
- +Scripting-first workflow enables consistent runs across many targets
- +Export options cover FITS and TIFF with controllable bit depth
- –Alignment threshold tuning needs iteration for each capture set
- –UI-first navigation is slower than scripted runs for bulk processing
- –Some advanced steps rely on knowing the right preprocessing order
- –Large stacks can increase throughput time on constrained systems
Astrophotography workflow engineers
Standardize stacking pipelines across observatory PCs
Repeatable stacks with fewer edits
Processing leads for outreach programs
Batch process mixed quality capture sets
Higher keeper rate per batch
Show 2 more scenarios
R&D teams testing capture parameters
Compare threshold settings across nights
Faster parameter iteration cycles
Pipeline configuration makes it practical to test alignment and rejection settings against different seeing conditions.
Data teams publishing astronomy imagery
Export analysis-ready FITS and TIFF stacks
Fewer format conversion steps
Controlled export options support consistent container format and bit depth for downstream tools.
Best for: Fits when teams need repeatable, scriptable stacking runs with strict frame acceptance and standardized exports.
Conclusion
After evaluating 10 moon stacking software, PixInsight stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
Frequently Asked Questions About Moon Stacking Software
Which tool automates batch frame rejection based on per-frame registration quality maps for lucky imaging sequences?
How should a team integrate moon stacking outputs into a wider processing pipeline with scripting or batch execution?
When does interactive tuning matter more than fully automated frame selection in lunar stacks?
What breaks if a workflow requires strict repeatability across sessions with the same calibration, alignment, gating, and export settings?
How do tools handle FITS containers, intermediate artifacts, and export targets for downstream review or re-stacking?
Which tool provides a concrete way to orchestrate multi-step calibration and registration for batch runs instead of treating each stage manually?
How do teams manage data model and project-level configuration when multiple operators process the same capture set?
What are the tradeoffs for a team that needs FWHM-driven quality gating versus registration-quality-map ranking?
Which tool supports lunar-specific derotation as part of the alignment and stacking workflow?
When a workflow needs an additional curation or publishing layer around stack results instead of more image processing, which tool fits?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
How to Choose the Right Moon Stacking Software
Moon stacking software options differ most in how reliably they turn a pile of images into consistent results, especially around Frame alignment and how much of the workflow they automate. We look for control over quality decisions in Quality thresholding, not just prettier previews.
Frame alignment quality
Why it matters
Frame alignment quality determines whether stars and lunar detail stay sharp across the stack. If alignment is weak, the final moon will look smeared even when other settings look correct.
How to check
Load a short sample burst and run a stack with default alignment. Compare zoomed-in edges and small craters with and without alignment; ask whether the tool shows an alignment score or error preview.
Quality thresholding and frame rejection
Why it matters
Quality thresholding and frame rejection reduce blur and bad moments from the final stack. That matters for moon footage where turbulence changes frame to frame.
How to check
Use a clip that includes both sharp and soft moments, then try two different quality thresholds. Inspect whether rejected frames are actually the blurrier ones and whether the output stabilizes as you tighten the threshold.
Sharpness ranking method transparency
Why it matters
Sharpness ranking affects which frames rise to the top when you use selection. Clear ranking behavior helps you avoid a stack that favors noise over detail.
How to check
Pick a dataset and choose a mode that ranks frames by sharpness, then view the list or metrics. Ask what the ranking is based on and confirm it correlates with visual sharpness in the preview.
Output format and bit depth handling
Why it matters
Output format and bit depth handling controls how much tonal detail survives stacking and post-processing. If the tool clips or downconverts unexpectedly, lunar gradients and contrast can degrade.
How to check
Run the same stack and export, then compare histogram/tonality in a viewer. Confirm the tool lets you keep the native dynamic range through export, and note any forced conversion.
Automation for batch moon stacks
Why it matters
Automation for batch moon stacks matters when you process many clips from different sessions. If settings don’t carry over cleanly, results become inconsistent.
How to check
Create a batch run with two or three clips and verify the same stacking parameters are applied consistently. Check whether presets save your alignment and quality decisions for reuse.
Extensible configuration and presets
Why it matters
Extensible configuration and presets let you codify your approach across targets and conditions. That reduces trial-and-error and helps keep output consistent over time.
How to check
In a demo, set custom options for alignment and rejection, then save them as a preset. Re-run on a new clip and confirm the preset reproduces the same behavior, not just similar output.
Red flags
- Alignment looks good only in preview, but exports are smeary
- Frame rejection changes the result wildly with small threshold tweaks
- Exports lose tonal detail due to forced conversions
Fit by situation
- If you process short capture bursts with mixed turbulence, prioritize Frame alignment quality.
- If you want repeatable results across many clips, prioritize Automation for batch moon stacks.
- If you do your own post-processing, prioritize Output format and bit depth handling.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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