Analysis of color Image Enhancement Using DWT, Wavelet Shrinkageand FHE Methods

2017 ◽  
Vol 7 (8) ◽  
pp. 56
Author(s):  
Ashish Dwivedi ◽  
Nirupma Tiwari
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Human Perception ◽  
Histogram Equalization ◽  
Wavelet Shrinkage ◽  
Visual Appearance ◽  
Enhancement Method ◽  
Fuzzy Histogram ◽  
Rgb Image

Image enhancement (IE) is very important in the field where visual appearance of an image is the main. Image enhancement is the process of improving the image in such a way that the resulting or output image is more suitable than the original image for specific task. With the help of image enhancement process the quality of image can be improved to get good quality images so that they can be clear for human perception or for the further analysis done by machines.Image enhancement method enhances the quality, visual appearance, improves clarity of images, removes blurring and noise, increases contrast and reveals details. The aim of this paper is to study and determine limitations of the existing IE techniques. This paper will provide an overview of different IE techniques commonly used. We Applied DWT on original RGB image then we applied FHE (Fuzzy Histogram Equalization) after DWT we have done the wavelet shrinkage on Three bands (LH, HL, HH). After that we fuse the shrinkage image and FHE image together and we get the enhance image.

scholarly journals Histogram Adjustment of Images for Improving Photogrammetric Reconstruction

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4654
Author(s):  
Piotr Łabędź ◽  
Krzysztof Skabek ◽  
Paweł Ozimek ◽  
Mateusz Nytko
Keyword(s):  
Image Enhancement ◽  
High Efficiency ◽  
Color Image ◽  
Histogram Equalization ◽  
Reconstruction Accuracy ◽  
Reconstruction Process ◽  
Reference Models ◽  
Color Models ◽  
Selection Of

The accuracy of photogrammetric reconstruction depends largely on the acquisition conditions and on the quality of input photographs. This paper proposes methods of improving raster images that increase photogrammetric reconstruction accuracy. These methods are based on modifying color image histograms. Special emphasis was placed on the selection of channels of the RGB and CIE L*a*b* color models for further improvement of the reconstruction process. A methodology was proposed for assessing the quality of reconstruction based on premade reference models using positional statistics. The analysis of the influence of image enhancement on reconstruction was carried out for various types of objects. The proposed methods can significantly improve the quality of reconstruction. The superiority of methods based on the luminance channel of the L*a*b* model was demonstrated. Our studies indicated high efficiency of the histogram equalization method (HE), although these results were not highly distinctive for all performed tests.

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.

Color Medical Image Enhancement Using Y-H Model and Wavelet Homomorphic Filtering

2013 ◽  
Vol 411-414 ◽  
pp. 1020-1024
Author(s):  
Hua Liang ◽  
Zhen Tao Zhou ◽  
Hao Feng ◽  
Li Jun Ding ◽  
Ju Ping Gu ◽  
...  
Keyword(s):  
Image Enhancement ◽  
Medical Image ◽  
Color Image ◽  
Color Space ◽  
Inverse Transformation ◽  
Homomorphic Filtering ◽  
Enhancement Method ◽  
Rgb Color Space ◽  
Medical Image Enhancement

Color medical images are widely used in the field of medical diagnosis. Image enhancement is one of the most important pretreatment methods which can enhance the quality of images. In this paper, a novel color image enhancement method using Y-H model and wavelet homomorhpic filtering is put forward. The chromaticity numbers matrix and intensity numbers matrix of color images are get using Young-Helmholtz (YH) transform. The chromaticity numbers matrix remains unchanged. Wavelet homomorphic filtering method is used to process intensity numbers matrix . The enhanced intensity numbers matrix and formerly chromaticity numbers matrix are processed by Y-H inverse transformation and disply in RGB color space. The method put forward in the paper is successfully used in color medical image enhancement. Experimental results show that the method have characteristics of nondistortion, better visual effect.

Several Color Image Enhancement Method Comparison

2013 ◽  
Vol 380-384 ◽  
pp. 3770-3773
Author(s):  
Ting Ting Huang ◽  
Yuan Li ◽  
Zhen Xiang Xie
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Method Comparison ◽  
Objective Evaluation ◽  
Histogram Equalization ◽  
Color Images ◽  
Simulation Experiments ◽  
Analysis Process ◽  
Color Image Enhancement ◽  
Enhancement Method

In this paper, the image analysis process, based on the characteristics of color images, were used histogram equalization, homomorphism filtering, Retinex multistage optimization and Zadeh-X transform for image processing, the use of simulation experiments, compared several methods in the image enhancement application, experimental results are presented and compared using several methods of objective evaluation.

Perbandingan Performa Histogram Equalization untuk Peningkatan Kualitas Gambar Minim Cahaya pada Android

2020 ◽  
Vol 12 (2) ◽  
pp. 80-88
Author(s):  
Claudia Kenyta ◽  
Daniel Martomanggolo Wonohadidjojo
Keyword(s):  
Image Enhancement ◽  
Light Condition ◽  
Histogram Equalization ◽  
Low Light ◽  
Adaptive Histogram Equalization ◽  
Enhancement Method ◽  
Better Than

When the photos are taken in low light condition, the quality of the results will not meet their expectation. Image Enhancement method can be used to enhance the quality of the photos taken in low light condition. One of the algorithms used is called Histogram Equalization (HE), that works using Histogram basis. The superiority of HE algorithm in enhancing the quality of the photos taken in low light condition is the simplicity of the algorithm itself and it does not need a high specification device for the algorithm to run. One variant of HE algorithm is Contrast Limited Adaptive Histogram Equalization (CLAHE). This paper shows the implementation of HE algorithm and its performance in enhancing the quality of photos taken in low light condition on Android based application and the comparison with CLAHE algorithm. The results show that, HE algorithm is better than CLAHE algorithm.

scholarly journals Image Enhancement Using Weighted Bi-Histogram Equalization

2021 ◽  
Vol 15 ◽  
pp. 98-101
Author(s):  
Thaweesak Trongtirakul ◽  
Nattapong Phanthuna
Keyword(s):  
Signal Processing ◽  
Probability Density Function ◽  
Image Enhancement ◽  
Human Perception ◽  
Digital Signal ◽  
Histogram Equalization ◽  
Area Ratio ◽  
Original Image ◽  
Weighted Factor

Image enhancement is one of using in various digital signal processing areas. Advances in microcontrollers, microcomputers and computers have developed traditional algorithms in order to improve the quality of the resulting image and have implied many avenues to the design of new innovations using various techniques. This paper proposes contrast enhancement using weighted bi-histogram equalization based on distributed area ratio. Moreover, this technique must use a weighted factor which is calculated by the ratio of the histogram distribution. Likewise, an original image will be equalized by the modification of the probability density function of the gray levels. As result of the experiment, the contrast of resulting image is improved for implement and human perception – as well as also reduces the absolute mean brightness error (AMBE) than the traditional technique of image enhancement.

A Modified Multi Scale Retinex with Color Restoration Algorithm for Automatic Enhancement of Landsat-5 Remote Sensing Image

2011 ◽  
Vol 341-342 ◽  
pp. 893-897
Author(s):  
Gui Zhou Wang ◽  
Guo Jin He
Keyword(s):  
Image Enhancement ◽  
Dynamic Range ◽  
Color Constancy ◽  
Human Perception ◽  
Histogram Equalization ◽  
Image Processing Algorithm ◽  
Multi Scale ◽  
Dynamic Range Compression ◽  
Restoration Algorithm ◽  
Color Restoration

The retinex is a human perception based image processing algorithm which provides color constancy and dynamic range compression. The multi scale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. But the MSRCR results suffer from lower global brightness and partial color distortion. In order to improve the MSRCR method, this paper presents a modified MSRCR algorithm to Landsat-5 image enhancement considering percent liner stretch and histogram adjustment. Finally, the effect of modified MSRCR method on Landsat-5 image enhancement is analyzed and the comparison with other color adjustment methods such as gamma correction and histogram equalization is reported in the experimental results.

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