A Novel Approach for Compression of Images Captured using Bayer Color Filter Arrays

TL;DR

This paper introduces a new image compression method tailored for Bayer filter array images in digital cameras, reversing traditional stages to improve quality and reduce complexity.

Contribution

It presents a novel compression approach that reverses the order of interpolation and compression, utilizing transform algorithms for non-interpolated images.

Findings

Outperforms conventional methods across various ratios

Provides better image quality at lower complexity

Reduces luminance data used in compression

Abstract

We propose a new approach for image compression in digital cameras, where the goal is to achieve better quality at a given rate by using the characteristics of a Bayer color filter array. Most digital cameras produce color images by using a single CCD plate, so that each pixel in an image has only one color component and therefore an interpolation method is needed to produce a full color image. After the image processing stage, in order to reduce the memory requirements of the camera, a lossless or lossy compression stage often follows. But in this scheme, before decreasing redundancy through compression, redundancy is increased in an interpolation stage. In order to avoid increasing the redundancy before compression, we propose algorithms for image compression in which the order of the compression and interpolation stages is reversed. We introduce image transform algorithms, since non interpolated images cannot be directly compressed with general image coders. The simulation results show that our algorithm outperforms conventional methods with various color interpolation methods in a wide range of compression ratios. Our proposed algorithm provides not only better quality but also lower encoding complexity because the amount of luminance data used is only half of that in conventional methods.