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Most Influential CVPR 1988 Paper · 2026-03 edition

Evaluation Of Quantization Error In Computer Vision

B. R. Kamgar-Parsi and B. Z. Kamgar-Parsi

Venue
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 1988
Recognition
Most Influential CVPR 1988 Paper (Rank No. 14)
Edition
2026-03
Impact factor
4
Certificate ID
2a4e8bdb7c41f392

Abstract

The authors develop the mathematical tools for the computation of the average error due to quantization. They can be used in estimating the actual error occurring in the implementation of a method. Also derived is the analytic expression for the probability density of error distribution of a function of an arbitrarily large number of independently quantized variables. The probability of the error of the function to be within a given range can thus be obtained accurately. In analyzing the applicability of an approach; it is necessary to determine whether the approach is capable of withstanding the quantization error. If it is not, then regardless of the accuracy with which the experiments are carried out, the approach will yield unacceptable results. The tools developed can be used in the analysis of the applicability of a given algorithm, hence revealing the intrinsic limitations of the approach.<>

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