Image Processing using Smooth Ordering of its Patches
Idan Ram, Michael Elad, Israel Cohen

TL;DR
This paper introduces a novel image processing method that reorders image patches into a sequence to facilitate effective denoising and inpainting through simple 1D smoothing techniques.
Contribution
It presents a new approach that transforms image restoration into a patch reordering problem solved via a shortest path, enabling improved image recovery.
Findings
Effective in denoising and inpainting tasks
Reordering patches improves image regularity
Simple 1D smoothing yields promising results
Abstract
We propose an image processing scheme based on reordering of its patches. For a given corrupted image, we extract all patches with overlaps, refer to these as coordinates in high-dimensional space, and order them such that they are chained in the "shortest possible path", essentially solving the traveling salesman problem. The obtained ordering applied to the corrupted image, implies a permutation of the image pixels to what should be a regular signal. This enables us to obtain good recovery of the clean image by applying relatively simple 1D smoothing operations (such as filtering or interpolation) to the reordered set of pixels. We explore the use of the proposed approach to image denoising and inpainting, and show promising results in both cases.
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