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Based on PCNN low-contrast gray-scale image enhancement methods and their evaluation

Author: WuBaiQiu
Tutor: ZhangJunYing
School: Xi'an University of Electronic Science and Technology
Course: Applied Computer Technology
Keywords: Pulse Coupled Neural Network Image Enhancement Grayscale image Evaluate
CLC: TP391.41
Type: Master's thesis
Year: 2006
Downloads: 411
Quote: 4
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Abstract


This subject is mainly engaged in Pulse Coupled Neural network (Pulse - Coupled Neural Networks, hereinafter referred to as the PCNN) theory research on the application of the digital image processing, specific examine it in the application of image enhancement. The project funded by the national natural science foundation of China, belongs to the basic theory research. PCNN is put forward in recent years a new type of network, belongs to the third generation of the neural network. Based on PCNN work principle and action mechanism of the deep analysis, in this paper, low contrast gray image enhancement algorithm based on PCNN. The algorithm applied the related properties of PCNN, and combined with the idea of histogram equalization enhancement algorithm has realized the overall image enhancement, and by using PCNN lateral inhibition and capture the characteristics of the local enhancement is realized. For the algorithm to make objective and fair evaluation of this paper, the application of a large number of other methods for contrast experiment, at the same time consulted a variety of evaluation methods of subjective and objective, and make the subjective and objective comprehensive evaluation. Compared with the traditional method, the algorithm in improving the overall contrast of the image at the same time, realizes the local contrast enhancement, in both the subjective evaluation and objective evaluation in the side, have achieved good results.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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