JPEG Meets PDE-based Image Compression
Sarah Andris, Joachim Weickert, Tobias Alt, and Pascal Peter

TL;DR
This paper introduces a hybrid image compression method combining JPEG and PDE-based inpainting, specifically using edge-enhancing diffusion, to improve reconstruction quality and provide new insights into region-based inpainting.
Contribution
It presents a novel hybrid codec that sparsifies JPEG blocks and reconstructs them with PDE inpainting, emphasizing region-based known data and corner regions for improved results.
Findings
Outperforms standard JPEG in quality
First to use regions instead of pixels as known data
Provides new insights into corner region importance
Abstract
Inpainting-based image compression is emerging as a promising competitor to transform-based compression techniques. Its key idea is to reconstruct image information from only few known regions through inpainting. Specific partial differential equations (PDEs) such as edge-enhancing diffusion (EED) give high quality reconstructions of image structures with low or medium texture. Even though the strengths of PDE- and transform-based compression are complementary, they have rarely been combined within a hybrid codec. We propose to sparsify blocks of a JPEG compressed image and reconstruct them with EED inpainting. Our codec consistently outperforms JPEG and gives useful indications for successfully developing hybrid codecs further. Furthermore, our method is the first to choose regions rather than pixels as known data for PDE-based compression. It also gives novel insights into the…
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