SIH26166: Multi-modal, Sun angle and scale invariant image correspondence using Chandrayaan-2 optica — SIH 2026

SIH26166: Multi-modal, Sun angle and scale invariant image correspondence using Chandrayaan-2 optica — SIH 2026

What they'll ask you

11

Generated from the brief's own wording and the competition's published rules — never from a guess about what this ministry prefers.

The specific programming languages or frameworks required?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
The exact format of the input and output image files?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Has any part of this been shown at a previous event, hackathon or college project?
The guidelines are explicit: your solution must not have appeared in any previous event or programme, of any sort. A recycled project is what a team under time pressure reaches for.

8 more— the ones a panel gets to if there is time

The brief asks for image loading and preprocessing. How would you build that?
Decoded from SIH26166 itself — A module to load source and reference lunar optical images from Chandrayaan-2 datasets. The brief asks for it by name.
The brief asks for feature matcher. How would you build that?
Decoded from SIH26166 itself — An algorithm that identifies and matches key points between images despite lighting and angle differences. The brief asks for it by name.
The brief asks for geometric transformation. How would you build that?
Decoded from SIH26166 itself — A component that warps the source image to align with the reference coordinate system. The brief asks for it by name.
The brief asks for accuracy evaluator. How would you build that?
Decoded from SIH26166 itself — A calculator that measures performance using metrics like RMSE, inlier match count, and inlier ratio. The brief asks for it by name.
Why not use what already exists? Name the closest thing to this that is already running.
A team that has not named the alternative themselves is answering this for the first time in the room.
Which single thing will you demonstrate end to end, start to finish, with nothing skipped?
Ours, not a rule: a narrow thing that fully works survives questioning better than a broad thing that half works. If nobody on the team can name it, that is the finding.
Show me this working: the evaluators will check if your software achieves sub-pixel accuracy and maintains a uniform distribution of match points across the images.
This is the evaluator read for your problem statement, decoded from the brief's own wording.
Show me this working: they will also review your registered output products and evaluation metrics like RMSE or inlier ratio.
This is the evaluator read for your problem statement, decoded from the brief's own wording.

Take this to an AI

Pick what you are about to do and copy the prompt. It carries the organisers' own wording, the constraints they never spell out, and an instruction not to invent requirements they never set.

Who has this problem, what already exists, and what you would have to find out.

# Context: India's Smart India Hackathon 2026

I am on a student team entering SIH 2026. Problem statement SIH26166, set by Indian Space Research Organisation(ISRO).
Its official title, word for word: "Multi-modal, Sun angle and scale invariant image correspondence using Chandrayaan-2 optical images (OHRC, TMC and IIRS)"
Theme: Space Technology. Category: software.

In plain terms: A software tool that aligns different Chandrayaan-2 lunar images by finding matching points, handling different lighting, angles, and scales to achieve sub-pixel accuracy.

## The organisers' full description, verbatim

Background Image Registration is the process of aligning two or more images of the same scene taken at different times, from different viewpoints, or by different sensors into a common coordinate system. It has two main components: • Source Image (Moving): The image that is to be geometrically transformed to align with the reference image. • Reference Image (Fixed): The target image about which source image is to be geometrically transformed. Description The process of lunar images registration involves finding match points between source and reference image and then aligning the source image with the reference image. The key challenges involved in this process are as follows: • Illumination variation: Illumination variation refers to changes in sun azimuth and elevation effect on the surface lighting conditions that affect the appearance of the lunar surface features which is hard to correlate. • Viewpoint variation: It refers to geometric distortions caused by different camera positions/orientations capturing the same scene. Objects appear shifted, scaled, rotated, or perspective-distorted depending on observing angle. • Scale Variation: Lunar imaging missions operate at vastly different altitudes and at different spatial resolutions. This creates scale ratios. Expected Solution Generic software solution for finding correspondence between Chandrayaan-2 acquired optical images and Lunar reference images with a sub-pixel accuracy of source image maintaining uniform distribution across the images. • Software and registered product with corresponding match points. • Evaluation metric (eg. RMSE, inlier match count, inlier ratio, etc.)

## What the brief never says

- The specific programming languages or frameworks required
- The exact format of the input and output image files
## Constraints that are not negotiable

- The judged build is a prototype demonstrated in roughly 36 hours by students, not a product.
- A jury evaluates it against this problem statement's own wording, not against general merit.
- We submit on sih.gov.in; the problem statement number and title above must match exactly.
- Your solution must not have appeared in any previous event or programme, of any sort.
- The organisers attached a dataset, so build against theirs rather than inventing one.

## What I want from you

1. Who actually has this problem in India, and what they do about it today.
2. What already exists — government systems, open-source projects, published research — that we should not rebuild.
3. For each item under 'what the brief never says', what the realistic answer is likely to be and how I could verify it.
4. The two or three things about this domain that a student team would get wrong without local knowledge.
## How to answer

- Everything above between quotation marks is the organisers' own wording. Treat it as the requirement.
- Do NOT invent requirements the brief does not state. If something matters and is not stated, say so and ask me, rather than assuming.
- Where you are inferring rather than reading, mark it as your inference.
- Do not guess what this ministry wants from its name. Its wording above is the only evidence.

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Problem statement facts assembled by Wynit from Indian Space Research Organisation(ISRO)'s published brief for SIH 2026.
The plain-English summary, the list of parts and the evaluator read are our interpretation of that text; the quoted title and the full description are theirs.