Image Processing using Smooth Ordering of its Patches
This addresses image restoration for applications like photography, but appears incremental as it builds on patch-based methods.
The paper tackles image denoising and inpainting by reordering image patches into a shortest path and applying 1D smoothing, showing promising results.
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.