scholarly journals Comparative Study of Different Image Enhancement Techniques

2012 ◽  
Vol 2 (3) ◽  
pp. 131-133
Author(s):  
Saruchi Garg ◽  
Madan Lal
Keyword(s):  
Comparative Study ◽  
Image Enhancement ◽  
Imaging Modality ◽  
Visual Quality ◽  
Low Contrast ◽  
Contrast Image

The main purpose of image enhancement is to bring out detail that is hidden in an image or to increase contrast in a low contrast image. Image enhancement techniques provide a multitude of choices for improving the visual quality of images. Appropriate choice of such techniques is greatly influenced by the imaging modality, task at hand and viewing conditions. This paper analyses the performance of some of existing image enhancement algorithms. The performance of algorithms are evaluated  both qualitatively and quantitatively.

scholarly journals Image Enhancement using Wavelet Fusion for Medical Image Processing

2019 ◽  
Vol 9 (1) ◽  
pp. 2663-2667
Keyword(s):  
Image Enhancement ◽  
Medical Image ◽  
Medical Images ◽  
Discrete Wavelet ◽  
Low Contrast ◽  
Adaptive Fusion ◽  
Improved Performance ◽  
Medical Image Enhancement ◽  
Contrast Image

Medical Image Enhancement Low contrast is the active study area that the obtained pictures suffer from noise and low contrast. Age of capturing equipment, bad illumination circumstances are the low contrast medical images. Thus, techniques of contrast improved performance are used before being used to enhance the contrast of medical images. Within a tiny range of pixel concentrations, contrast improvement algorithms enhance low contrast image. Low contrast image enhancement is accomplished using Equalization of Contrast Limited Adaptive Histogram. CLAHE image enhancement is used to enhance the quality of medical images with low contrast. DWT image, sub-bands such as LL, LH, HL, HH are decomposed. 2D Adaptive fusion image on discrete wavelet transformation is used to fuse the main and CLAHE output images. The efficiency of the output is calculated using merged image entropy and PSNR. It is discovered that the visual content of low contrast medical pictures is enhanced effectively on the basis of 2D DWT and adaptive Fusion.

Research on low contrast image enhancement technology

2021 ◽  
Author(s):  
Jiale Yao ◽  
Xiangsuo Fan ◽  
Yixun Chen ◽  
Wuchao Li
Keyword(s):  
Image Enhancement ◽  
Low Contrast ◽  
Enhancement Technology ◽  
Contrast Image

How Good is Too Good? A Subjective Study on Over Enhancement of Images

2021 ◽  
Vol 2021 (29) ◽  
pp. 83-88
Author(s):  
Sahar Azimian ◽  
Farah Torkamani Azar ◽  
Seyed Ali Amirshahi
Keyword(s):  
Image Quality ◽  
High Contrast ◽  
Current Image ◽  
Low Contrast ◽  
Image Dataset ◽  
Long Time ◽  
Reference Images ◽  
Subjective Study ◽  
Contrast Image

For a long time different studies have focused on introducing new image enhancement techniques. While these techniques show a good performance and are able to increase the quality of images, little attention has been paid to how and when overenhancement occurs in the image. This could possibly be linked to the fact that current image quality metrics are not able to accurately evaluate the quality of enhanced images. In this study we introduce the Subjective Enhanced Image Dataset (SEID) in which 15 observers are asked to enhance the quality of 30 reference images which are shown to them once at a low and another time at a high contrast. Observers were instructed to enhance the quality of the images to the point that any more enhancement will result in a drop in the image quality. Results show that there is an agreement between observers on when over-enhancement occurs and this point is closely similar no matter if the high contrast or the low contrast image is enhanced.

Low-contrast image enhancement using spatial contextual similarity histogram computation and color reconstruction

2020 ◽  
Vol 357 (18) ◽  
pp. 13941-13963
Author(s):  
Kankanala Srinivas ◽  
Ashish Kumar Bhandari ◽  
Anurag Singh
Keyword(s):  
Image Enhancement ◽  
Low Contrast ◽  
Contrast Image

An Image Enhancement Method Based on the Coal Mine Monitoring System

2012 ◽  
Vol 468-471 ◽  
pp. 204-207
Author(s):  
Zhen Chong Wang ◽  
Yan Qin Zhao
Keyword(s):  
Image Enhancement ◽  
Coal Mine ◽  
Impulse Noise ◽  
Histogram Equalization ◽  
Video Monitor ◽  
Low Contrast ◽  
Adaptive Histogram Equalization ◽  
Enhancement Method ◽  
Special Environment

For the low illumination and low contrast in the coal mine, images captured from the video monitor system sometimes are not so clear to help the related personal monitoring the production and safety of the mine. According to the special environment of coal mine, an image enhancement method was presented. In this method the impulse noise which is the mainly noise in the coal mine was first reduced with median filtering, then the low contrast and illumination was greatly improved with the improved adaptive histogram equalization. Experiments show that this method can improve the quality of images underground effectively.

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