Work place: ECE Department, Moradabad Institute of Technology, Moradabad (U.P.), India
E-mail: shyam.mtec@gmail.com
Website:
Research Interests: Image Processing, Image and Sound Processing, Image Manipulation, Image Compression, Computer Graphics and Visualization
Biography
Shyam Lal, male, is Associate Professor in the Department of Electronics & Communication Engineering, Moradabad Institute of Technology, Moradabad (U.P.), India. He has more than 11.5 years of Teaching & Research experience. He has published more than 44 research papers in the area of Digital Signal & Image Processing and Wireless Communication at International/National Journals & Conferences. He has been Guest Editor of International Journal of Signal & Imaging System Engineering (IJSISE), Inderscience Publishers. His area of interest includes Digital Image Processing, Digital Signal Processing and Wireless Communication.
DOI: https://doi.org/10.5815/ijigsp.2013.05.04, Pub. Date: 28 Apr. 2013
This paper presents enhancement of hyperspectral real world images using hybrid domain approach. The proposed method consists of three phases: In first phase the discrete wavelet transform is applied and approximation coefficient is selected. In second phase approximation coefficient of discrete wavelet transform of image is process by automatic contrast adjustment technique and in third phase it takes logarithmic of output of second phase and after that adaptive filtering is applied for image enhancement in frequency domain. To judge the superiority of proposed method the image quality parameters such as measure of enhancement (EME) and measure of enhancement factor (EMF) is evaluated. Therefore, a better value of EME and EMF implies that the visual quality of the enhanced image is good. Simulation results indicates that proposed method provides better results as compared to other state-of-art contrast enhancement algorithms for hyperspectral real world images. The proposed method is efficient and very effective method for contrast enhancement of hyperspectral real world images. This method can also be used in different applications where images are suffering from different contrast problems.
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