期刊
IMAGE AND VISION COMPUTING
卷 28, 期 3, 页码 458-466出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.imavis.2009.07.007
关键词
Neural network; Image filtering; Impulse detector; Impulse noise
A new efficient approach to detect the impulse noise from the corrupted image using feed forward neural network (FFNN) is presented. A modified version of the arithmetic mean filter is proposed to remove the detected impulse noise. The performance of proposed noise detection approach is analyzed using the performance measures such as False Alarm Ratio (FAR), Missed Noise (MN) pixels and Falsely Detected Noise (FDN) pixels. The simulation results show that these performances are robust even at higher percentage of noise. The filtered result is compared with the other recent approaches in terms of Peak Signal to Noise Ratio (PSNR). The proposed method produces remarkably good results both in quantitative measures and qualitative judgments of image quality. (C) 2009 Elsevier B.V. All rights reserved.
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