scholarly journals Image Enhancement using Recursive Standard Intensity Deviation Based Clipped Sub Image Histogram Equalization

2019 ◽  
Vol 9 (2) ◽  
pp. 3933-3937
Keyword(s):  
Image Enhancement ◽  
Histogram Equalization ◽  
Light Conditions ◽  
Low Light ◽  
Image Histogram ◽  
Output Image ◽  
Standard Intensity ◽  
Underwater Image ◽  
Image Inspection ◽  
Low Exposure

The low exposure image enhancement has become indispensable inimage processing for better visibility. The most challenging in image enhancement is especially to curtail overenhancement problems. This paper presents a method, performs the separation of the histogram based on respective standard intensity deviation value and then recursively equalizes all sub histograms independently. The over-enhancement problem is minimized by this method. It applies more in an underwater image, because of its low light conditions. The experiment results are analyzed in terms of entropy and output image inspection. The proposed method results show significant improvement over earlier recursive based histogram equalization algorithms.

Research on the Image Enhancement Algorithm of Pointer Instrument under Inadequate Light

2014 ◽  
Vol 615 ◽  
pp. 248-254 ◽  
Author(s):  
Lu Zhang ◽  
Jin Lin Zhang ◽  
Ting Rui ◽  
Yue Wang ◽  
Yan Nan Wang
Keyword(s):  
Image Processing ◽  
Image Enhancement ◽  
Traditional Method ◽  
Histogram Equalization ◽  
Light Conditions ◽  
Low Light ◽  
Homomorphic Filtering ◽  
The Impact ◽  
Image Details ◽  
Enhancement Algorithm

For image processing, the recognition of pointer instrument’s reading by computer vision highly depends on brightness. An image enhancement algorithm based on homomorphic filtering and histogram equalization is proposed in order to reduce the impact of low-light conditions on images of pointer instrument. It combines the methods of spatial with frequency domain, which enhances the image contrast and highlights the image details as well. Compared with the traditional method, the experiments show that the proposed method can eliminate the effect of inadequate light and also perform well in enhancing the image quality.

scholarly journals Image Enhancement using Recursive Separate Standard Intensity Deviation Based Clipped Sub Image Histogram Equalization

2020 ◽  
Vol 9 (3) ◽  
pp. 782-787
Keyword(s):  
Threshold Value ◽  
Histogram Equalization ◽  
Specific Region ◽  
Recursive Algorithms ◽  
Image Histogram ◽  
Standard Intensity ◽  
Equalization Algorithm ◽  
Low Exposure ◽  
Average Information ◽  
Mammogram Images

To improve image contrast, this paper introduces a recursive separate standard intensity deviation based clipped sub image histogram equalization method. This is an extension of standard intensity deviation value based sub image histogram equalization algorithm, in terms of histogram separation and equalization. In existing equalization methods do not effectively utilizes the information from different region in equalization process. In this scheme, the image histogram is bisected based on standard intensity deviation value. The further separation is carried out based on the specific region threshold value and the resulting four sub histograms are equalized individually. This is an effective method for enhancing, low exposure, medical and mammogram images and for addressing the over-enhancement problem. The performance evaluation of the proposed method is presented with the help of average information and visual quality assessment and the proposed algorithm outperforms existing recursive algorithms based on histogram equalization.

scholarly journals A Review on Underwater Image Enhancement

2020 ◽  
pp. 27-34
Author(s):  
Mohammad Moiz Ashrafi ◽  
Apurv Verma ◽  
Abhishek Badholia
Keyword(s):  
Image Enhancement ◽  
Deep Water ◽  
Research Area ◽  
Light Variation ◽  
Low Light ◽  
Underwater Image

While capturing underwater image there are lot of imposed due to low light, light variation, poor visibility. Photography is about light, but since water has an a lot more prominent density than air — around 800 times more noteworthy not all wavelengths of light travel similarly well inside it. This implies as we go down into deep water, we lose the shades of the range one by one. This is the reason submerged photographs lose all the red and orange hues even at a genuinely shallow profundity and appear to be increasingly more blue as we go deep in water, henceforth captured image need enhancement. It’s a vital research area, in this paper we will review different techniques of underwater image enhancement.

scholarly journals Noise Suppression and Contrast Enhancement via Bayesian Residual Transform (BRT) in Low-Light Conditions

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Audrey G. Chung ◽  
Alexander Wong
Keyword(s):  
Contrast Enhancement ◽  
Image Enhancement ◽  
Noise Suppression ◽  
State Of The Art ◽  
Light Conditions ◽  
Low Light ◽  
Preliminary Results ◽  
Denoised Image

Very low-light conditions are problematic for current robotic visionalgorithms as captured images are subject to high levels of ISOnoise. We propose a Bayesian Residual Transform (BRT) model forjoint noise suppression and image enhancement for images capturedunder these low-light conditions via a Bayesian-based multiscaleimage decomposition. The BRT models a given image as thesum of residual images, and the denoised image is reconstructedusing a weighted summation of these residual images. We evaluatethe efficacy of the proposed BRT model using the VIP-LowLightdataset, and preliminary results show a notable visual improvementover state-of-the-art denoising methods.

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