胡椒鹽雜訊濾除之比例積分濾波器設計

The PI-Remover Design for Salt-and-Pepper Noise Elimination

辜信榮(Shin-Jung Gu)

指導教授 ： 廖梨君

朝陽科技大學/資訊學院/資訊工程系/碩士(2009年)

摘要

本論文提出以比例積分控制器之概念，來設計一濾除胡椒鹽雜訊之濾波器，稱之為比例積分濾波器(PI-remover)，同時在雜訊偵測上與補償目標值是利用修改後之自適性中值濾波器為依據，而濾除雜訊方面則是結合了比例積分控制器的概念，針對雜訊點將欲補償之誤差值及累積誤差值乘上比例參數與積分參數，以達到補償的效果。由實驗結果可知，利用比例積分濾波器所重建之影像品質與效能，皆比傳統的自適性中值濾波器來得優異，並且能有效的濾除胡椒鹽脈衝雜訊達90%。

關鍵字

胡椒鹽雜訊 ； 比例積分控制器 ； 中值濾波器 ； 自適性中值濾波器

並列摘要

This thesis proposes a new filtering scheme _PI remover for effectively eliminating the salt-and-pepper noise of images. The PI-remover can be created straightforwardly based on the concept of Proportional-Integral (PI)controller. Similar as the design of PI-controller, the PI-remover also has the proportional parameter and integral parameter , that are used to weight the noisy pixels. The modified adaptive-median filter (AMF) is used to detect the possible noisy pixels. The noisy pixels are compensated to approach an objective value by running few iterations of the PI-remover’s compensation loop. The experimental results demonstrate that the PSNR of the restored images by using PI-remover is significantly improved as compared with that by using AMF. The PI-remover can still perform well as the noise level increase to 90%.

並列關鍵字

salt-and-pepper noise ； adaptive median filter ； median filter ； PI-controller

參考文獻

[14] Farzam Farbiz, Mohammad Bager Menhaj, Seyed A. Motamedi, and Martin T. Hagan A, “ New Fuzzy Logic Filter for Image Enhancement”, IEEE Transaction on System Man, and Cybernetics—part b: Cybernetics, vol. 30, no. 1, Feb. 2000, pp.110-119.

[1] A. Bovik, Handbook of Image and Video Processing. New York: Academic, 2000.

[4] Raymond H. Chan, Chung-Wa Ho, and Mila Nikolova, “Salt & pepper noise removal by median-type noise detectors and detail-preserving regularization”, IEEE Transaction on Image Processing, vol. 14, no. 10, Oct. 2005, pp. 1479-1485.

[5] Thomas A. Nodes and Neal C. Gallagher, Jr., “The output distribution of medium type filters”, IEEE Transaction on Communication, vol. 4, no. 4, May 1984, pp. 532-541.

[6] Pei-Eng Ng and Kai-Kuang Ma, ”A switching median filter with boundary discriminative noise detection extremely corrupted images,” IEEE Transaction on Image Processing, vol. 15, no. 6, Jun. 2006, pp.1506-1516.