Evaluation of Quantization Error in Computer Vision
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.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Kamgar-Parsi and Kamgar-Parsi. "Evaluation of Quantization Error in Computer Vision." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1988. doi:10.1109/CVPR.1988.196214Markdown
[Kamgar-Parsi and Kamgar-Parsi. "Evaluation of Quantization Error in Computer Vision." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1988.](https://mlanthology.org/cvpr/1988/kamgarparsi1988cvpr-evaluation/) doi:10.1109/CVPR.1988.196214BibTeX
@inproceedings{kamgarparsi1988cvpr-evaluation,
title = {{Evaluation of Quantization Error in Computer Vision}},
author = {Kamgar-Parsi, Behrooz and Kamgar-Parsi, Behzad},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1988},
pages = {52-60},
doi = {10.1109/CVPR.1988.196214},
url = {https://mlanthology.org/cvpr/1988/kamgarparsi1988cvpr-evaluation/}
}