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Contrast and Luminance Enhancement Using Discrete Shearlet Transform, Discrete Cosine Transform And Filtering Technique


Miss. Priyanka V. Pawade , BAPURAO DESHMUKH COLLEGE OF ENGINEERING SEWAGRAM; Dr. M. A. Gaikwad, Principal B.D.C.O.E. Sewagram; Prof. A. W. Hignikar, Assitant Prof. Electronics & Telecomm.B.D.C.O.E Sewagram


Image Enhancement, discrete shearlet transform, discrete cosine transform, filter


Image enhancement is a process of improving the perception or interpretability of the information in image. The main objective of image enhancement is to improve some characteristics of an image to make it visually better for human viewer. These are the various types of image enhancement techniques like contrast enhancement etc. Contrast enhancement technique includes the methods like Histogram Equalization (HE), Brightness preserving Bi-Histogram Equalization(BBHE), Dualistic sub-image Histogram Equalization (DSIHE), Minimum mean Brightness Bi-Historgram Equalization (MMBEBHE). Contrast enhancement improves the perceptibility of an image by changing the pixel intensity of input image. This paper presents review of different image contrast enhancement techniques. In this project, we enhance the images by applying local transformation and filtering technique on input image. This method improves the quality of the image with minimal unexpected artifacts. Experimental results show that our method outperforms other methods in majority cases. The subjective and objective performance evaluation shows that the proposed enhancement method yields better results without changing image original color in comparison with the conventional methods. In this project, a novel method for image contrast and luminance enhancement is proposed based on Discrete Shearlet Transform (DST) and Discrete Cosine Transform (DCT) for color images. In order to obtain high contrast enhancement, the RGB image is first converted into HSV (Hue, Saturation and Value) color space. The converted hue color channel and V (luminance value) component of the HSV color image is only taken into the account for DST and DCT decomposition. After decomposition we use filter to smooth the histogram. Finally, we get enhanced image by reconstructing RGB values from HSV color space.

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Manuscript Id :IJSTEV3I1151
Published in :Volume : 3, Issue : 1
Publication Date: 01/08/2016
Page(s): 342-347
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