Paper
28 December 2000 Comparison of multiple compression cycle performance for JPEG and JPEG 2000
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Abstract
Ideally, when the same set of compression parameters are used, it is desirable for a compression algorithm to be idempotent to multiple cycles of compression and decompression. However, this condition is generally not satisfied for most images and compression settings of interest. Furthermore, if the image undergoes cropping before recompression, there is a severe degradation in image quality. In this paper we compare the multiple compression cycle performance of JPEG and JPEG2000. The performance is compared for different quantization tables (shaped or flat) and a variety of bit rates, with or without cropping. It is shown that in the absence of clipping errors, it is possible to derive conditions on the quantization tables under which the image is idempotent to repeated compression cycles. Simulation results show that when images have the same mean squared error (MSE) after the first compression cycle, there are situations in which the images compressed with JPEG2000 can degrade more rapidly compared to JPEG in subsequent compression cycles. Also, the multiple compression cycle performance of JPEG2000 depends on the specific choice of wavelet filters. Finally, we observe that in the presence of cropping, JPEG2000 is clearly superior to JPEG. Also, when it is anticipated that the images will be cropped between compression cycles when using JPEG2000, it is recommended that the canvas system be used.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rajan L. Joshi, Majid Rabbani, and Margaret A. Lepley "Comparison of multiple compression cycle performance for JPEG and JPEG 2000", Proc. SPIE 4115, Applications of Digital Image Processing XXIII, (28 December 2000); https://doi.org/10.1117/12.411570
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CITATIONS
Cited by 14 scholarly publications.
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KEYWORDS
JPEG2000

Image compression

Digital filtering

Quantization

Gold

Image quality

Image filtering

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