ANALYSIS AND STATISTICS OF IMAGE HISTOGRAMS.
Keywords:
Histogram, image, frequency distribution, intensity, pixel, color, gray image, bing, element, set.Abstract
The analysis and statistical data of image histograms are studied in the article. It discusses how histograms can be used to interpret image statistics in a visual format and their role in diagnosing various problems. Histograms are important to avoid poor real-time imaging by modern digital devices. It helps to improve image quality by detecting errors during the imaging process and is used for further image processing.
References
H. Abdul-Rahman and N. Chernov. Fast and numerically stable circle fit. Journal of Mathematical Imaging and Vision 49, 289–295 (2014).
M. Ahmed and R. Ward. A rotation invariant rule-based thinning algorithm for character recognition. IEEE Transactions on PatternAnalysis and Machine Intelligence 24(12), 1672–1678 (2002).
N. Ahmed. How I came up with the Discrete Cosine Transform.Digital Signal Processing 1, 4–5 (1991).
S. J. Ahn. “Least Squares Orthogonal Distance Fitting of Curves and Surfaces in Space”, vol. 3151 of “Lecture Notes in Computer Science”. Springer (2004).
Al-Sharadqah and N. Chernov. Error analysis for circle fitting algorithms. Electronic Journal of Statistics 3, 886–911 (2009).
L. Alvarez, P.-L. Lions, and J.-M. Morel. Image selective smoothing and edge detection by nonlinear diffusion (II). SIAM Journal on Numerical Analysis 29(3), 845–866 (1992).
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