Top 10 Best Moon Stacking Software of 2026

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.

The main tradeoff is that deep tuning of alignment and quality thresholds can require iterative runs to match a dataset’s seeing conditions and exposure strategy. It fits best when a team already has consistent capture conventions and wants deterministic stacking results across nights, including standardized output selection like FITS versus TIFF and 8-bit versus 16-bit.

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.

A common tradeoff is that advanced results depend on capture quality and calibration hygiene because the selection stage cannot fix severe tracking drift or extreme saturation. AutoStakkert! fits situations where large SER or AVI captures need repeatable batch stacks for different nights without manual frame-by-frame curation.

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.

A tradeoff is that automation depth is strongest inside the alignment and sharpening pipeline, not in broader batch provisioning across multiple nights, targets, or capture sessions. RegiStax fits situations where a small team runs repeated capture-to-result cycles and wants tight visual feedback on alignment and sharpening without building additional automation around it. It also works when stacking multiple captures for one target and iterating on frame rejection criteria and wavelet layer settings to converge on a consistent appearance.

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.

For moon stacking workflows, it can support front-end curation like organizing capture sets, quality notes, and publishing results, while image processing stays outside its feature set. Teams that need a staging area for final deliverables and repeatable layouts can use it as a control layer around the stack output.

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.

Radix supports throughput-oriented batch processing so teams can run large capture sets with consistent thresholds. Output control focuses on producing analysis-friendly artifacts for downstream review and re-stacking rather than only generating a single composite.

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.

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.

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.

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.

It also includes sharpening-oriented steps that operate on the stacked output to improve perceived detail without changing the raw alignment inputs. Automation is comparatively limited, so repeated sessions usually rely on saving project settings and using its batch-oriented operations rather than an external API.

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.

StarTools also supports FITS and common export targets for downstream stacking, so capture results can be reprocessed with repeatable settings. It is best used when a team wants tight control over frame selection, calibration steps, and stack export settings rather than relying on automated defaults.