Paper
5 July 1995 Investigation into the geometric consequences of processing substantially compressed images
Udo Tempelmann, Zubbi Nwosu, Roland M. Zumbrunn
Author Affiliations +
Abstract
One of the major driving forces behind digital photogrammetric systems is the continued drop in the cost of digital storage systems. However, terrestrial remote sensing systems continue to generate enormous volumes of data due to smaller pixels, larger coverage, and increased multispectral and multitemporal possibilities. Sophisticated compression algorithms have been developed but reduced visual quality of their output, which impedes object identification, and resultant geometric deformation have been limiting factors in employing compression. Compression and decompression time is also an issue but of less importance due to off-line possibilities. Two typical image blocks have been selected, one sub-block from a SPOT image and the other is an image of industrial targets taken with an off-the-shelf CCD. Three common compression algorithms have been chosen: JPEG, Wavelet, and Fractal. The images are run through the compression/decompression cycle, with parameter chosen to cover the whole range of available compression ratios. Points are identified on these images and their locations are compared against those in the originals. These results are presented to assist choice of compression facilities after considerations on metric quality against storage availability. Fractals offer the best visual quality but JPEG, closely followed by wavelets, imposes less geometric defects. JPEG seems to offer the best all-around performance when you consider geometric and visual quality, and compression/decompression speed.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Udo Tempelmann, Zubbi Nwosu, and Roland M. Zumbrunn "Investigation into the geometric consequences of processing substantially compressed images", Proc. SPIE 2486, Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision II, (5 July 1995); https://doi.org/10.1117/12.213131
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image compression

Wavelets

Fractal analysis

Visualization

Image processing

Visual compression

Detection and tracking algorithms

RELATED CONTENT

Interband prediction method for subband image coding
Proceedings of SPIE (March 03 1995)
Regional adaptive resolution-based fractal block coding
Proceedings of SPIE (July 08 1998)
Spatial quantization via local texture masking
Proceedings of SPIE (March 18 2005)
Perceptually lossless fractal image compression
Proceedings of SPIE (February 27 1996)
LIDAR data compression using wavelets
Proceedings of SPIE (October 28 2005)

Back to Top