Enhancement of Hyperspectral Real World Images Using Hybrid Domain Approach
Author(s) -
Shyam Lal,
Rahul Kumar
Publication year - 2013
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2013.05.04
Subject(s) - hyperspectral imaging , artificial intelligence , image (mathematics) , logarithm , computer science , pattern recognition (psychology) , computer vision , measure (data warehouse) , discrete wavelet transform , contrast (vision) , image quality , mathematics , phase (matter) , wavelet transform , wavelet , algorithm , data mining , physics , mathematical analysis , quantum mechanics
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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