Presentation + Paper
30 August 2017 High bit depth infrared image compression via low bit depth codecs
Evgeny Belyaev, Claire Mantel, Søren Forchhammer
Author Affiliations +
Abstract
Future infrared remote sensing systems, such as monitoring of the Earth’s environment by satellites, infrastructure inspection by unmanned airborne vehicles etc., will require 16 bit depth infrared images to be compressed and stored or transmitted for further analysis. Such systems are equipped with low power embedded platforms where image or video data is compressed by a hardware block called the video processing unit (VPU). However, in many cases using two 8-bit VPUs can provide advantages compared with using higher bit depth image compression directly. We propose to compress 16 bit depth images via 8 bit depth codecs in the following way. First, an input 16 bit depth image is mapped into 8 bit depth images, e.g., the first image contains only the most significant bytes (MSB image) and the second one contains only the least significant bytes (LSB image). Then each image is compressed by an image or video codec with 8 bits per pixel input format. We analyze how the compression parameters for both MSB and LSB images should be chosen to provide the maximum objective quality for a given compression ratio. Finally, we apply the proposed infrared image compression method utilizing JPEG and H.264/AVC codecs, which are usually available in efficient implementations, and compare their rate-distortion performance with JPEG2000, JPEG-XT and H.265/HEVC codecs supporting direct compression of infrared images in 16 bit depth format. A preliminary result shows that two 8 bit H.264/AVC codecs can achieve similar result as 16 bit HEVC codec.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Evgeny Belyaev, Claire Mantel, and Søren Forchhammer "High bit depth infrared image compression via low bit depth codecs", Proc. SPIE 10403, Infrared Remote Sensing and Instrumentation XXV, 104030A (30 August 2017); https://doi.org/10.1117/12.2275542
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CITATIONS
Cited by 3 scholarly publications and 2 patents.
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KEYWORDS
Image compression

Infrared imaging

Infrared radiation

Infrared sensors

Remote sensing

Video

Video compression

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