Bayer CFA Pattern Compression With JPEG XS

Thomas Richter

doi:10.1109/TIP.2021.3095421

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Bayer CFA Pattern Compression With JPEG XS

2021-01-01

DOI：10.1109/TIP.2021.3095421

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Abstract

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While traditional image compression algorithms take a full three-component color representation of an image as input, capturing of such images is done in many applications with Bayer CFA pattern sensors that provide only a single color information per sensor element and position. In order to avoid additional complexity at the encoder side, such CFA pattern images can be compressed directly without prior conversion to a full color image. In this paper, we describe a recent activity of the JPEG committee (ISO SC 29 WG 1) to develop such a compression algorithm in the framework of JPEG XS. It turns out that it is important to understand the development process from CFA patterns to full color images in order to optimize the image quality of such a compression algorithm, which we will also describe shortly. We introduce (1) a novel decorrelation step upfront processing (the so-called Star-Tetrix transform), along with (2) a pre-emphasis function to improve the compression efficiency of the subsequent compression algorithm (here, JPEG XS). Our experiments clearly indicate a gain over a RGB compression workflow in terms of complexity and quality (between 1.5dB and more than 4dB depending on the target bitrate). A comparison is also made with other state-of-the-art CFA compression techniques.

Keywords:

Image coding

Image color analysis

Transform coding

Interpolation

Color

Decorrelation

Complexity theory

Image coding

JPEG XS

CFA pattern compression

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