JOURNAL ARTICLE

Backwards Compatible JPEG Stereoscopic High Dynamic Range Imaging

Abstract

In this paper we introduce Stereoscopic High Dynamic Range (SHDR) Imagery which is a novel tecnique that combines high dynamic range imaging and stereoscopy. Stereoscopic imaging captures two images representing the views of both eyes and allows for better depth perception. High dynamic range (HDR) imaging is an emerging technology which allows the capture, storage and display of real world lighting as opposed to traditional imagery which only captures a restricted range of light due to limitation in hardware capture and displays. HDR provides better contrast and more natural looking scenes. One of the main challenges that needs to be overcome for SHDR to be successful is an efficient storage format that compresses the very large sizes obtained by SHDR if left uncompressed; stereoscopic imaging requires the storage of two images and uncompressed HDR requires the storage of a floating point value per colour channel per pixel. In this paper we present a number of SHDR compression methods that are backward compatible with traditional JPEG, stereo JPEG and JPEG-HDR. The proposed methods can encode SHDR content to little more than that of a traditional LDR image and the backward compatibility property encourages early adopters to adopt the format since their content will still be viewable by any of the legacy viewers.

Keywords:
Stereoscopy High dynamic range JPEG Computer science High-dynamic-range imaging Uncompressed video Computer vision Computer graphics (images) Artificial intelligence Dynamic range Tone mapping Backward compatibility Pixel Data compression Video processing

Metrics

7
Cited By
0.00
FWCI (Field Weighted Citation Impact)
17
Refs
Citation Normalized Percentile
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Citation History

Topics

Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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