JPEG quantizer optimization for financial document images

Mahmoud R. El-Sakka; Khaled S. Hassanein; Mohamed S. Kamel

doi:10.1117/12.323207

1 October 1998 JPEG quantizer optimization for financial document images

Mahmoud R. El-Sakka, Khaled S. Hassanein, Mohamed S. Kamel

Proceedings Volume 3460, Applications of Digital Image Processing XXI; (1998) https://doi.org/10.1117/12.323207
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

In this paper, two schemes for optimizing the JPEG quantizer are investigated. The first scheme starts from a given quantization-table and executes a sub-optimal search for quantization-table parameters. Those parameters, when changed by a pre-specified incremental step-size, result in the most optimal move towards decreasing (increasing) the compressed file-size, with a minimal increase (maximum decrease) of error. This procedure is repeated, until a pre- specified file-size is reached. The second scheme is based on performing a mapping from the JPEG default quantization- table to an optimized one. This mapping adapts the default quantization-table to the statistics of the DCT coefficients of the image at hand. The superiority of these two optimized JPEG quantizers is established in terms of the visual quality of their reconstructed images. This was done by running comparative visual image quality experiments involving 20 human subjects. These optimized quantizers were also demonstrated to result in a higher level of machine image quality, by improving the accuracy of cheque amount reading applications. Experimental results indicate that the second optimization scheme yields a higher level of visual image quality, while requiring a fraction of the processing time used by the first scheme.

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Mahmoud R. El-Sakka, Khaled S. Hassanein, and Mohamed S. Kamel "JPEG quantizer optimization for financial document images", Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); https://doi.org/10.1117/12.323207

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KEYWORDS

Visualization

Image compression

Image quality

Image visualization

Optimization (mathematics)

Detection and tracking algorithms

Visual compression

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