scholarly journals A Comparative Study of Histogram Equalization Based Image Enhancement Techniques for Brightness Preservation and Contrast Enhancement

2013 ◽  
Vol 4 (5) ◽  
pp. 11-25 ◽  
Author(s):  
Omprakash Patel ◽  
Yogendra P. S. Maravi ◽  
Sanjeev Sharma
Keyword(s):  
Comparative Study ◽  
Contrast Enhancement ◽  
Image Enhancement ◽  
Histogram Equalization ◽  
Brightness Preservation

Contrast Enhancement Using Optimum Threshold Selection

2020 ◽  
Vol 8 (3) ◽  
pp. 96-118
Author(s):  
Geeta Rani ◽  
Monika Agarwal
Keyword(s):  
Contrast Enhancement ◽  
Maximum Entropy ◽  
Dynamic Range ◽  
Threshold Value ◽  
Histogram Equalization ◽  
Threshold Method ◽  
Essential Information ◽  
Low Contrast ◽  
Brightness Preservation ◽  
Double Threshold

In the recent era, a boom was observed in the field of information retrieval from images. Digital images with high contrast are sources of abundant information. The gathered information is useful in the precise detection of an object, event, or anomaly captured in an image scene. Existing systems do uniform distribution of intensities and apply intensity histogram equalization. These improve the characteristics of an image in terms of visual appearance. The problem of over enhancement and the increase in noise level produces undesirable visual artefacts. The use of Otsu's single threshold method in existing systems is inefficient for segmenting an image with multiple objects and complex background. Additionally, these are incapable to improve the yield of the maximum entropy and brightness preservation. The aforementioned limitations motivate us to propose an efficient statistical pipelined approach, the Range Limited Double Threshold Weighted Histogram Equalization (RLDTWHE). This approach is an integration of Otsu's double threshold, dynamic range stretching, weighted distribution, adaptive gamma correction, and homomorphic filtering. It provides optimum contrast enhancement by selecting the best appropriate threshold value for image segmentation. The proposed approach is efficient in the enhancement of low contrast medical MRI images and digital natural scene images. It effectively preserves all essential information recorded in an image. Experimental results prove its efficacy in terms of maximum entropy preservation, brightness preservation, contrast enhancement, and retaining the natural appearance of an image.

scholarly journals A Novel Technique for Automatic Image Enhancement using HTHET Approach

2019 ◽  
Vol 8 (1) ◽  
pp. 26-31
Author(s):  
V. Murali ◽  
T. Venkateswarlu
Keyword(s):  
Contrast Enhancement ◽  
Image Enhancement ◽  
Information Content ◽  
Optimization Method ◽  
Histogram Equalization ◽  
Original Image ◽  
Enhancement Technique ◽  
Novel Technique ◽  
Equalization Technique ◽  
Histogram Transformation

Image enhancement techniques are methods used for producing images with better quality than the original image. None of the existing methods increase the information content of the image, and are usually of little interest for subsequent automatic analysis of images. In this paper, automated Image Enhancement is achieved by carrying out Histogram techniques. Histogram equalization (HE) is a spatial domain image enhancement technique, which effectively enhances the contrast of an image. We make use of Transformation and Hyperbolization techniques for automatic image enhancement. However, while it takes care of contrast enhancement, a modified histogram equalization technique, Histogram Transformation and Hyperbolization Equalization Technique (HTHET) using optimization method is proposed using EQHIST and LINHIST.

Sign in / Sign up

Export Citation Format

Share Document