GITNUXSOFTWARE REVIEW
Science ResearchTop 9 Best Planetary Stacking Software of 2026
Compare planetary stacking software tools for processing planetary images. Review key features and tradeoffs for choosing RegiStax, Orbitus, or PixInsight.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
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Framework: Features 40% · Ease 30% · Value 30%
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RegiStax is the best choice for individual imagers who want interactive planetary stacking because its wavelet sharpening updates with a direct preview tied to the stacked result, while PixInsight is better for experienced users needing a parameterized, reproducible operator pipeline across large runs.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
RegiStax
Wavelet sharpening with immediate preview tied directly to the stacked result for planetary contrast control.
Best for: Fits when individual imagers need interactive planetary stacking control and wavelet tuning without building a pipeline.
Orbitus
Editor pickJob-style workflow reuse keeps alignment and stacking settings consistent across batch targets.
Best for: Fits when imaging teams need consistent, batchable planetary stacks across nights with minimal reconfiguration.
PixInsight
Editor pickProcessing graph operators that keep alignment and rejection stages parameterized and reproducible across runs.
Best for: Fits when experienced imagers need operator-level control across large planetary stacks.
Comparison Table
RegiStax
vertical specialistFree image processing software for stacking planetary and lunar images.
Wavelet sharpening with immediate preview tied directly to the stacked result for planetary contrast control.
RegiStax is a dedicated planetary stacking and processing workflow built around manual and semi-automatic quality sorting, then alignment star registration. The pipeline supports common planetary steps like alignment, stacking with rejection, and basic post-stack enhancement outputs in formats suitable for further editing.
Its core advantage is a tight feedback loop between wavefront-style sharpening controls and preview-driven frame selection. RegiStax also includes calibration frame handling for dark and flat workflows used to improve signal consistency before stacking.
- +Interactive frame quality sorting with fast visual feedback during selection
- +Star-based alignment workflow geared for planetary scales and small fields
- +Stacking with rejection modes designed for noisy captures and seeing variability
- +Built-in post-stack sharpening and wavelet controls for planetary detail
- –Desktop-only workflow without an API or automation surface for pipelines
- –Limited support for full multi-channel calibration complexity beyond basic frames
- –FITS-centric capture formats can require extra pre-processing outside RegiStax
- –Large batch throughput is slower than script-driven stacks in other tools
Planetary astrophotographers
Stack high-frame-rate planet video frames
Cleaner, more detailed stack
Amateur astrophotographers
Reject blurred frames before stacking
Less blur, more consistent sharpness
Show 2 more scenarios
Astrophotographers refining results
Apply wavelet sharpening after stacking
More controlled detail
Run multi-scale wavelet sharpening and denoising on the finished stack for controlled contrast.
Astrophotographers processing sessions
Reuse workflows across repeated captures
Less rework, more repeatability
Apply a repeatable sorting and stacking approach across similar sessions, then tune sharpening per target.
Best for: Fits when individual imagers need interactive planetary stacking control and wavelet tuning without building a pipeline.
Orbitus
vertical specialistGPU-accelerated all-in-one planetary processing application combining stacking and wavelet sharpening.
Job-style workflow reuse keeps alignment and stacking settings consistent across batch targets.
Orbitus handles the core planetary stacking loop with quality sorting, alignment preparation, and batchable stacking runs that reduce per-session setup. The workflow emphasizes predictable exports so downstream tools get consistent FITS or TIFF results for further processing. It is most compatible with users who store captures as RAW or converted frames and want a repeatable processing path for each target.
The tradeoff is reduced interactive flexibility during processing compared with capture-to-result apps that constantly expose fine-grained controls per step. Orbitus fits situations where an imaging team needs to re-run the same alignment and stacking sequence across nights, then compare outputs without rebuilding the pipeline.
- +Repeatable batch workflow reduces per-target manual tuning
- +Quality ranking helps prune frames before alignment and stacking
- +Consistent output exports support downstream calibration and analysis
- +Job-style processing fits multi-target throughput during imaging runs
- –Interactive per-frame tweaking is limited versus desktop imaging apps
- –Setup requires more up-front choices than simple click-and-stack tools
- –Automation depth depends on file-based workflows rather than device control
Amateur astrophotography teams
Process multiple captures per target
Fewer rework iterations
Raspberry Pi or workstation operators
Run unattended overnight stacks
Higher overnight throughput
Show 1 more scenario
Planetary imaging analysts
Compare stack results over time
Cleaner A-B comparisons
Re-run the same processing sequence to compare outputs from different capture conditions.
Best for: Fits when imaging teams need consistent, batchable planetary stacks across nights with minimal reconfiguration.
PixInsight
enterprisePaid astronomical image-processing platform with registration and integration tools.
Processing graph operators that keep alignment and rejection stages parameterized and reproducible across runs.
PixInsight supports the full planetary workflow in one environment, including frame evaluation, alignment, and stacking with multiple rejection strategies. It runs alignment and combine operations as deterministic processing steps, which makes repeated experiments and parameter sweeps practical. The workflow stays close to FITS-centric astronomy handling, which reduces friction when raw frames already live in that ecosystem.
A tradeoff appears in setup time and workflow discipline, because tuning rejection, registration settings, and calibration handling requires more parameter attention than button-based tools. PixInsight fits situations where planetary sequences include high frame counts and the goal is repeatable, operator-level control across multiple nights and targets.
- +Deterministic operator pipeline for repeatable planetary experiments
- +High-control star registration with configurable alignment models
- +Advanced frame rejection and combine options tuned for planetary data
- +FITS-centered workflow with reliable export controls
- –Steeper learning curve due to extensive parameter exposure
- –Batch automation requires scripting discipline rather than simple UI presets
- –Workflow setup takes longer than one-click planetary stackers
- –Some planetary-specific conveniences depend on community workflows
Visual planetary imagers
Tune alignment and rejection for detail
Higher apparent sharpness after stacking
Astro imaging power users
Run repeatable parameter sweeps nightly
Faster iteration on best parameters
Show 1 more scenario
Remote observatory teams
Standardize FITS processing across sessions
Consistent outputs across operators
A shared processing sequence reduces variation when data arrives from multiple sessions.
Best for: Fits when experienced imagers need operator-level control across large planetary stacks.
Astro Pixel Processor
SMBDesktop astrophotography processor with calibration, registration, and integration features.
Local alignment with controllable rejection settings that targets planet detail without requiring per-frame manual intervention.
Astro Pixel Processor is designed around a planetary sequence pipeline that starts with importing RAW or converted image sets, then selecting frames based on quality metrics, then performing star-based alignment. Integration runs through configurable rejection logic and combine modes, producing results tuned for either conservative or aggressive cleanup. The software also supports calibration-frame generation so dark, bias, and flat corrections can be applied consistently across large captures.
- +Quality ranking speeds frame selection for large planetary sequences
- +Global and local alignment options cover different seeing and motion cases
- +Configurable rejection controls reduce noise and outlier frames
- +Batch processing keeps settings consistent across multiple runs
- –Local alignment tuning takes practice to avoid overfitting artifacts
- –Workflow relies on well-organized image sets per target and session
- –Some advanced steps require deeper understanding of calibration inputs
- –Export and finishing steps may still need external color workflow
Lunar and planetary imagers
Stacks mixed seeing frames consistently
Sharper edges with fewer outliers
Astrophotography workflow operators
Batch process multiple captures nightly
Higher throughput per session
Show 2 more scenarios
Observers preparing calibration-ready stacks
Builds master calibration frames
Cleaner integration baseline
Calibration-frame generation applies consistent dark, bias, and flat corrections to the stack input.
High-detail planet finishers
Exports high-bit-depth results for finishing
More headroom for finishing
High-bit-depth exports preserve dynamic range for later sharpening and color adjustment steps.
Best for: Fits when planetary imagers need repeatable alignment and rejection across many capture sequences.
AstroSurface
vertical specialistAstronomy image-processing software with planetary stacking and sharpening tools.
Quality-guided planetary stacking that combines star registration style alignment with rejection during the combine stage.
AstroSurface runs astronomical image stacking for planetary imaging, with alignment and quality-based frame selection aimed at producing a single higher signal-to-noise result. It supports the standard planetary workflow of sorting frames, aligning across time, and stacking with common rejection strategies to reduce noise and artifacts.
- +Frame sorting and selection workflow fits typical planetary capture sessions
- +Alignment and stacking controls cover common planetary registration scenarios
- +Calibration frame handling supports cleaner final masters
- +Export pipeline targets standard imager formats like TIFF and FITS
- –Workflow breadth is focused on stacking rather than capture or observatory automation
- –Automation and API surface are limited for multi-night unattended runs
- –Advanced tuning requires iterative parameter adjustments for stable results
- –Batch throughput is constrained when processing many long capture sets
Planetary astrophotographers
Stack short exposures for higher sharpness
Sharper stacked planet image
Lunar imagers
Align and stack lunar video frames
Detailed lunar stack
Show 2 more scenarios
Solar imagers
Integrate solar frames into a stack
Stacked solar image
Align and refine solar capture sequences, then stack frames for a combined presentation-ready output.
Astrophotographers managing sessions
Repeat calibration and stacking exports
More consistent results
Apply repeatable calibration and stacking steps across sessions, then export consistent outputs per target.
Best for: Fits when planetary imagers need repeatable stacking and alignment control without building custom pipelines.
Eise.app
vertical specialistBrowser-based planetary image stacker using WebGPU for lucky imaging of solar system objects.
Star registration plus alignment verification gating before quality sorting and rejection.
Eise.app performs planetary stacking by taking aligned frames and running quality sorting, rejection, and combine steps to produce a higher signal-to-noise output. It is distinct for a workflow that centers on star registration and alignment checks before any stacking stage runs. The tool also handles calibration frame workflows and exports stacked results for further processing in common planetary imaging pipelines.
- +Star registration workflow makes alignment issues visible before stacking
- +Frame quality sorting reduces bad frames before rejection
- +Calibration frame handling supports repeatable master generation
- +FITS and TIFF export cover common planetary imaging handoff needs
- –Local alignment controls are harder to tune than global alignment
- –Some advanced rejection strategies are less configurable than specialist stacks
Planetary astrophotographers
Align frames then quality-sort and stack
Higher signal-to-noise output
Astrophotographers running repeat stacks
Process calibrated frames through stacking
Calibration-aware stacked output
Best for: Fits when small teams want repeatable planetary stacks with alignment checks and calibrated inputs.
Siril
SMBFree astronomical image-processing software with registration and stacking workflows.
Project-driven automation with command sequences for repeatable calibration and stacking across large planetary datasets.
Siril is a planetary imaging stacking tool that focuses on image calibration and stacking workflows tuned for astronomers. It supports alignment strategies and rejection-based stacking inside a project-style pipeline that works directly with FITS files.
- +FITS-first workflow keeps metadata and bit depth intact through stacking
- +Multiple alignment and stacking paths support different planetary conditions
- +Command-driven processing enables repeatable, batch re-runs
- +Built-in calibration stack building with consistent outputs
- –Workflow configuration requires astronomy-specific parameter discipline
- –Less suited to high-throughput automation with external orchestration layers
- –GUI-centered steps can slow complex multi-target batch setups
- –Output ergonomics depend on exporting into other tools for advanced finishing
Planetary imagers
Preprocess and stack selected frames
Sharper planetary image
Deep-sky astrophotographers
Calibrate and stack multiple exposures
Higher-signal integrated image
Show 2 more scenarios
Milky Way photographers
Register wide-field frames before stacking
Repeatable wide-field stack
Calibrate and register night-sky frames, then stack them into a consistent multi-image result.
Astrophotographers with inconsistent sets
Inspect, register, and reject bad inputs
Cleaner stack
Use frame inspection, registration, and rejection options to keep problematic frames out of the final combine.
Best for: Fits when planetary imagers need repeatable FITS calibration and stacking workflows without switching to multiple tools.
PIPP
vertical specialistPlanetary Imaging PreProcessor that prepares video frames for stacking applications.
Quality sorting based on per-frame image statistics supports repeatable selection before alignment and stacking.
PIPP provides fast preprocessing for astronomical imagery before stacking, with workflows built around frame cleanup, selection, and output formatting. It can crop, rotate, and re-center targets so downstream alignment stars and stacking tools start from consistent frames.
- +Frame filtering uses numeric image metrics for quick quality sorting.
- +Batch preprocessing supports cropping, rotation, and centering for consistent inputs.
- +Output options target stacking workflows with predictable formats and bit depth.
- +Automation-friendly command-line usage fits repeatable capture-to-stack runs.
- –Advanced alignment and derotation are not the main focus of the tool.
- –Quality thresholds require trial runs to avoid discarding useful frames.
Astrophotographers batching video inputs
Crop, rotate, and re-center stack-ready frames
Consistent frames for stacking
Planetary and lunar imagers
Filter frames using brightness metrics
Quality-filtered sequence
Best for: Fits when planetary capture runs need automated frame selection and standardized crops before stacking.
AutoStakkert!
vertical specialistPlanetary image stacker for aligning and combining video frames.
Local alignment and quality-based frame selection are combined to produce multiple stack outputs from one run.
AutoStakkert! builds a complete planetary stacking pipeline around FITS ingestion, automated frame scoring, and alignment star registration.
- +Automated quality sorting with selectable frame percentages for final stacks
- +Local alignment option improves results on datasets with field rotation artifacts
- +FITS-first workflow keeps planetary stacks consistent across camera setups
- +Transparent control of rejection strength helps tune output for different seeing
- –Setup requires learning mapping between alignment settings and stack outcomes
- –No native collaboration or RBAC controls for shared processing workspaces
- –Limited integration surface for automated pipelines compared with scripting-first ecosystems
- –Advanced modes can be time-consuming to tune across sessions
Planetary astrophotographers
Select and align sharp frames from video
Sharper stack for enhancement
Solar imagers
Combine selected solar capture frames
Stacked solar image
Show 2 more scenarios
Wide-field astrophotographers
Sort and align suitable frames for export
Quality-filtered Milky Way stack
Register a star-rich sequence and export a quality-filtered stack with improved star sharpness.
Astrophotographers running recurring sessions
Batch apply stacking to large capture sequences
More consistent processing
Apply an automated stacking workflow across multiple large sequences from similar observing sessions.
Best for: Fits when single-user planetary workflows need fast frame selection and alignment tuning without custom coding.
Conclusion
After evaluating 9 planetary stacking software, RegiStax 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 Planetary Stacking Software
How do Astro Pixel Processor and AutoStakkert! differ in frame selection and rejection control?
Which tool is better suited for a reproducible processing graph workflow: PixInsight or Orbitus?
When is PIPP the right preprocessing step before running a planetary stack in another tool?
What breaks if RegiStax is used only for manual wavelet tuning without a structured pipeline for batch calibration?
Where does Eise.app fall short compared with AstroSurface for alignment verification and stacking control?
How does Siril’s command-sequence automation compare with PixInsight’s operator-level reproducibility?
Which tool supports a star-registration and alignment-check workflow before stacking: Eise.app or Astro Pixel Processor?
When should alignment and derotation be handled upstream instead of inside the stacking tool?
How do calibration frame workflows differ across Siril and RegiStax?
What integration and data-format expectations apply when moving between these tools using FITS and export pipelines?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
How to Choose the Right Planetary Stacking Software
We separate options in planetary stacking software by how they handle alignment and rejection choices across many frames. The biggest day-to-day differences show up in frame alignment accuracy, rejection method behavior, and whether results stay reproducible with the same configuration.
Subpixel alignment controls
Why it matters
Subpixel alignment controls determine whether fine shifts and small distortions get handled without smearing detail. For planetary sequences, this directly affects edge sharpness and contrast.
How to check
Run a short test on the included sample set or your own burst where motion is present, then compare results with alignment refinement turned on vs off. In the output preview, look for crisper boundaries and less blur at high magnification.
Frame rejection and quality sorting
Why it matters
Frame rejection and quality sorting decides which moments survive when seeing conditions vary. This can protect detail or accidentally drop good frames, depending on the rules.
How to check
Use a clip with noticeably uneven frames, then try at least two rejection settings (more strict vs more tolerant). Confirm which frames get excluded by reviewing the flagged/kept thumbnails or any per-frame scores it reports.
Configurable workflow and re-run reproducibility
Why it matters
A configurable workflow and re-run reproducibility matters when you need the same result months later or across datasets. Hidden defaults make it hard to trust comparisons.
How to check
Set parameters for one run, then re-run with the same inputs and confirm the outputs match visually and numerically. If the tool exports settings (or a project file), verify you can recreate the exact run from that artifact.
Batch processing for many sequences
Why it matters
Batch processing affects time-to-results when you stack multiple planets, sessions, or wavelengths. It also reduces mistakes from repeating manual steps.
How to check
Queue two or more sequences and confirm the tool keeps consistent alignment and rejection settings per batch item. Watch for unexpected parameter resets and verify outputs are produced for every item without manual babysitting.
Import/export formats and metadata preservation
Why it matters
Import/export formats and metadata preservation decide whether you can keep calibration context and review outputs in your normal pipeline. Losing key info forces extra manual work or unclear provenance.
How to check
Import a file format you regularly use, then export stacked outputs and check that timestamps, exposure-related metadata, and any project notes remain accessible. If the tool converts formats, verify it doesn’t change orientation or scale unexpectedly.
Red flags
- Results look sharper but change a lot between identical re-runs
- Rejection removes too many frames, leaving uneven smoothness
- Alignment settings are opaque or impossible to reproduce from exported settings
Fit by situation
- If you often stack bursts with variable seeing, prioritize frame rejection and quality sorting.
- If you need consistent outcomes across sessions, prioritize Configurable workflow and re-run reproducibility.
- If you process multiple nights in one go, prioritize Batch processing for many sequences.
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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