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Jain, Yogendra Kumar
- Image Sharpness and Contrast Enhancement with Noise Reduction using Logarithmic Image Processing Model with Modified Decision based Unsymmetric Trimmed Median Filter
Authors
1 Department of CSE, Samrat Ashok Technological Institute, Vidisha (M.P.), IN
Source
Digital Image Processing, Vol 4, No 16 (2012), Pagination: 902-909Abstract
Image enhancement is basic problem in the field of image processing & it can be subdivided into many categories like edge enhancement, smoothing, contrast enhancement, bright enhancement, sharpness enhancement etc. The classical approach treats the operations using linear systems which creates many computational problems and also does not match to human visual perception and interpretation logic. In this work we propose a LIP (Logarithmic Image Processing) technique in combination with MDBUTMF (Modified Decision Based Unsymmetric Trimmed Median Filter) for contrast and sharpness enhancement with capability to suppress the noise. LIP uses non-linear operations for image manipulation which are computationally effective. In LIP, image processing specific arithmetic operations are introduced which ensure that there is no loss of information in the form of ―out-of-range‖ pixel values. MDBUTMF is a very efficient median filter and it is capable of de-noising images which are corrupted with high density salt and pepper noise. Thus the combination of these techniques results in an efficient image enhancement algorithm. MDBUTMF is first applied to de-noise the input image. The de-noised image is further processed by LIP based enhancement methods to generate the final output. All the implementation work has been done in MATLAB 10.0 image processing tool box. Simulation results show a marked improvement in performance in terms of removal of noise, contrast, sharpness, detail enhancement, and Overall quality of image as compared to existing algorithms.Keywords
Image Enhancement, Sharpness Enhancement, Noise Reduction, LIP (Logarithmic Image Processing), Median Filter.- Adaptive approach for Image Fusion using Curvelet Transform and Genetic Algorithm
Authors
1 Department of Computer Science & Engineering at Samrat Ashok Technological Institute, Vidisha, M.P., IN
2 Department of Computer Science & Engineering at Samrat Ashok Technological Institute, Vidisha, M.P, IN
Source
Digital Image Processing, Vol 4, No 15 (2012), Pagination: 850-857Abstract
Although image fusion is a technique of merging two or more images that have consilient information to form a fused image which contains more accurate information of the image than any of the individual source images. In this paper, we proposed a multi-view and multi-modal Fusion, and Pixel level fusion approach. At first stage we perform feature extraction of image which plays a major role in the implementation of fusion approaches. Prior to the merging of images, salient features, present in all source images, are extracted using an appropriate feature extraction procedure. For the same we use transform domain texture feature Extraction (Curvelet) for better edge representation. After that fusion is performed on these extracted features vector by using genetic algorithm to get the more optimized combined image. Performance evaluation has been carried out of using the RMSE, PSNR and IQI. The results of the proposed method is compared with the existing techniques of image fusion using DWT. Experimental results shows that of curvelet transform and GA is better than DWT fusion method.
Keywords
Curvelet, Discrete Wavelet Transform, Feature Vectors, Genetic Algorithm, Image Fusion, Texture Feature Extraction.- Performance Analysis and Comparison of Image Compression Using DCT and Wavelets
Authors
1 Computer Science & Engineering, Samrat Ashok Technological Institute, Vidisha-464001 (M.P.), IN
2 Computer Science & Engineering, Laxminarayana College of Engineering, Bhopal (M.P.), IN