Novel method of image enhancement based on contrast pyramid

2007 ◽  
Author(s):  
Zhen-ming Yu ◽  
Fei Gao
Keyword(s):  
Image Enhancement ◽  
Novel Method

Image Enhancement

2020 ◽  
pp. 211-223
Author(s):  
Rasmita Lenka ◽  
Asimananda Khandual ◽  
Koustav Dutta ◽  
Soumya Ranjan Nayak
Keyword(s):  
Image Enhancement ◽  
Color Constancy ◽  
Correction Method ◽  
Color Correction ◽  
Dark Channel Prior ◽  
Post Processing ◽  
Dark Channel ◽  
Novel Method ◽  
Low Illumination ◽  
Human Eyes

This chapter describes a novel method to enhance degraded nighttime images by dehazing and color correction method. In the first part of this chapter, the authors focus on filtering process for low illumination images. Secondly, they propose an efficient dehazing model for removing haziness Thirdly, a color correction method proposed for color consistency approach. Removing nighttime haze technique is an important and necessary procedure to avoid ill-condition visibility of human eyes. Scattering and color distortion are two major problems of distortion in case of hazy image. To increase the visibility of the scene, the authors compute the preprocessing using WLS filter. Then the airlight component for the non-uniform illumination presents in nighttime scenes is improved by using a modified well-known dark-channel prior algorithm for removing nighttime haze, and then it uses α-automatic color equalization as post-processing for color correction over the entire image for getting a better enhanced output image free from haze with improved color constancy.

scholarly journals Finger Vein Segmentation from Infrared Images Based on a Modified Separable Mumford Shah Model and Local Entropy Thresholding

2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Marios Vlachos ◽  
Evangelos Dermatas
Keyword(s):  
Image Enhancement ◽  
Local Application ◽  
Local Entropy ◽  
Infrared Images ◽  
Vein Pattern ◽  
Finger Vein ◽  
Small Window ◽  
Minimization Procedure ◽  
Novel Method ◽  
Computationally Intensive

A novel method for finger vein pattern extraction from infrared images is presented. This method involves four steps: preprocessing which performs local normalization of the image intensity, image enhancement, image segmentation, and finally postprocessing for image cleaning. In the image enhancement step, an image which will be both smooth and similar to the original is sought. The enhanced image is obtained by minimizing the objective function of a modified separable Mumford Shah Model. Since, this minimization procedure is computationally intensive for large images, a local application of the Mumford Shah Model in small window neighborhoods is proposed. The finger veins are located in concave nonsmooth regions and, so, in order to distinct them from the other tissue parts, all the differences between the smooth neighborhoods, obtained by the local application of the model, and the corresponding windows of the original image are added. After that, veins in the enhanced image have been sufficiently emphasized. Thus, after image enhancement, an accurate segmentation can be obtained readily by a local entropy thresholding method. Finally, the resulted binary image may suffer from some misclassifications and, so, a postprocessing step is performed in order to extract a robust finger vein pattern.

scholarly journals Gray-Scale Image Dehazing Guided by Scene Depth Information

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Bo Jiang ◽  
Wanxu Zhang ◽  
Jian Zhao ◽  
Yi Ru ◽  
Min Liu ◽  
...  
Keyword(s):  
Image Enhancement ◽  
Physical Model ◽  
Color Image ◽  
Depth Information ◽  
Gray Scale ◽  
Image Dehazing ◽  
Guided Image Filter ◽  
Gray Scale Image ◽  
Novel Method ◽  
Scene Depth

Combined with two different types of image dehazing strategies based on image enhancement and atmospheric physical model, respectively, a novel method for gray-scale image dehazing is proposed in this paper. For image-enhancement-based strategy, the characteristics of its simplicity, effectiveness, and no color distortion are preserved, and the common guided image filter is modified to match the application of image enhancement. Through wavelet decomposition, the high frequency boundary of original image is preserved in advance. Moreover, the process of image dehazing can be guided by the image of scene depth proportion directly estimated from the original gray-scale image. Our method has the advantages of brightness consistency and no distortion over the state-of-the-art methods based on atmospheric physical model. Particularly, our method overcomes the essential shortcoming of the abovementioned methods that are mainly working for color image. Meanwhile, an image of scene depth proportion is acquired as a byproduct of image dehazing.

ADAPTIVE NONLINEAR IMAGE ENHANCEMENT OF GAUSSIAN DEGRADED IMAGES

2010 ◽  
Vol 10 (03) ◽  
pp. 365-393
Author(s):  
RAHUL GOWDA ◽  
SHALIN M. MEHTA ◽  
YUE YANG ◽  
BAOXIN LI
Keyword(s):  
Image Enhancement ◽  
Gabor Filter ◽  
Empirical Relationship ◽  
Objective Evaluation ◽  
Gabor Filters ◽  
Input Image ◽  
Digital Television ◽  
Extensive Evaluation ◽  
Blurred Image ◽  
Novel Method

An adaptive technique for nonlinear image enhancement using Gabor filters is proposed. A set of Gabor filters are employed to extract high-pass components from the blurred image and these components are then nonlinearly processed before adding back to the input image for enhancement. Further, we propose a novel method for fast blur estimation and we establish an empirical relationship between the estimated blur and the optimal Gabor filter parameters, resulting in an enhancement system that is adaptive to the degree of blur in the input image. Extensive evaluation, including both PSNR-based objective evaluation and subjective psychophysical tests, confirms the advantages of the proposed approach over existing state-of-the-art methods. This enhancement approach is especially targeted at digital television applications where image blur is present due to various reasons like compression and resolution up-conversion.

Local Statistic Enhancement of Digital Image Based on Genetic Algorithm

2013 ◽  
Vol 427-429 ◽  
pp. 1836-1840 ◽  
Author(s):  
Yong Zhuo Wu ◽  
Zhen Tu ◽  
Lei Liu
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Experimental Results ◽  
Computer Application ◽  
Novel Method ◽  
New Research

Iamge repair using the digital image processing technology has become a new research point in computer application. A novel method of local statistic enhancement based on genetic algorithm is proposed in this paper for the image enhancement. The modified amplified function are used as the jugement criterion, and the optimal paremeters are searched by the genetic algorithm. Experimental results show that the quality of images is improved dramatically by using this method.

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