A New Approach for B Ultrasound Images Enhancement

2013 ◽  
Vol 785-786 ◽  
pp. 1391-1394
Author(s):  
Chun Ying Pang ◽  
Qi Yu Jiao
Keyword(s):  
Clinical Practice ◽  
Image Enhancement ◽  
Ultrasound Images ◽  
Gray Level ◽  
Threshold Selection ◽  
New Approach ◽  
Fuzzy Algorithm ◽  
Enhancement Method

To make B ultrasound images clear, a new image enhancement method was studied.The study used an improved fuzzy algorithm based on gray-level to process B ultrasound images. And the process is largely simple by adding threshold selection which could meet different clinical demand. Several kinds of enhancement algorithms for B ultrasound images are evaluated and compared by using MATLAB to process the same image. The results after contrast show that the improved fuzzy algorithm is effective and achieved in clinical practice.

Study on Image Enhancement Technique of License Plate Recognition

2015 ◽  
Vol 738-739 ◽  
pp. 678-681
Author(s):  
Yu Bing Dong ◽  
Guang Liang Cheng ◽  
Ming Jing Li
Keyword(s):  
Image Enhancement ◽  
License Plate ◽  
Gray Level ◽  
License Plate Recognition ◽  
Median Filtering ◽  
Enhancement Technique ◽  
Enhancement Method ◽  
Basic Image

Various basic image enhancement techniques of License Plate Recognition are discussed and simulated with MATLAB. Through a lot of experiments, an improved image enhancement method is proposed by combining gray-level transformation and median filtering. The method can efficiently avoid interfere and enhance the contrast of image and obtain satisfying effects.

Frog and Haze Image Enhancement Using Improved Histogram Equalization Method in HIS Color Space

2014 ◽  
Vol 687-691 ◽  
pp. 3671-3674
Author(s):  
Dian Yuan Han
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Low Frequency ◽  
Histogram Equalization ◽  
Image Display ◽  
Gray Level ◽  
Mapping Algorithm ◽  
Enhancement Method ◽  
Gray Level Mapping ◽  
Weight Coefficients

This paper concerns the problem of frog and haze image enhancement. Images are often degreed due to the fog and haze condition. In this paper, an image enhancement method by using improved histogram equalization in HIS color space was put forward. Firstly, the image was transformed from RGB to HIS color space. Then the S and I components were treated with improved histogram equalization separately. When judging whether a gray level was to be merged with another, the weight coefficients with increased step were assigned to these low frequency gray levels according to their distance to the current gray level. Thus the excessive gray level merging was avoided. At the same time, a non-linear gray level mapping algorithm was proposed, which improved the contrast and brightness of the image. The experimental results show that our methods could keep the original colors and details of the image better, and they could improve the frog and haze image display effects significantly.

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.

Aliskiren, a Direct Renin Inhibitor, in Clinical Practice: A New Approach in the Treatment of Hypertension

2010 ◽  
Vol 8 (3) ◽  
pp. 344-362 ◽  
Author(s):  
Elisavet Moutzouri ◽  
Matilda Florentin ◽  
Moses S. Elisaf ◽  
Dimitri P. Mikhailidis ◽  
Evangelos N. Liberopoulos
Keyword(s):  
Clinical Practice ◽  
Renin Inhibitor ◽  
New Approach ◽  
Direct Renin Inhibitor ◽  
Treatment Of Hypertension

Underwater Image Enhancement Method Combining color and Luminance

2020 ◽  
Vol 13 ◽  
Author(s):  
ZHAO Baiting ◽  
WANG Feng ◽  
JIA Xiaofen ◽  
GUO Yongcun ◽  
WANG Chengjun
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Low Frequency ◽  
Brightness Enhancement ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method ◽  
Frequency Components ◽  
Image Contour ◽  
Objective Indicators

Background:: Aiming at the problems of color distortion, low clarity and poor visibility of underwater image caused by complex underwater environment, a wavelet fusion method UIPWF for underwater image enhancement is proposed. Methods:: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels, and balance the color of R, G and B channels by affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour. Results:: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information. Conclusion:: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

Experimental Validation of Minimax Entropy Principle in Ultrasound Images

2019 ◽  
Vol 12 (6) ◽  
pp. 487-493
Author(s):  
Neha Mehta ◽  
Svav Prasad ◽  
Leena Arya
Keyword(s):  
Region Of Interest ◽  
Ultrasound Images ◽  
Human Gallbladder ◽  
New Approach ◽  
Non Invasive ◽  
Entropy Principle ◽  
Significant Performance ◽  
Considerable Impact ◽  
Ultrasonic Devices ◽  
Measure Of Uncertainty

Ultrasound imaging is one of the non-invasive imaging, that diagnoses the disease inside a human body and there are numerous ultrasonic devices being used frequently. Entropy as a well known statistical measure of uncertainty has a considerable impact on the medical images. A procedure for minimizing the entropy with respect to the region of interest is demonstrated. This new approach has shown the experiments using Extracted Region Of Interest Based Sharpened image, called as (EROIS) image based on Minimax entropy principle and various filters. In this turn, the approach also validates the versatility of the entropy concept. Experiments have been performed practically on the real-time ultrasound images collected from ultrasound centers and have shown a significant performance. The present approach has been validated with showing results over ultrasound images of the Human Gallbladder.

scholarly journals Underwater Image Enhancement Based on Local Contrast Correction and Multi-Scale Fusion

2021 ◽  
Vol 9 (2) ◽  
pp. 225
Author(s):  
Farong Gao ◽  
Kai Wang ◽  
Zhangyi Yang ◽  
Yejian Wang ◽  
Qizhong Zhang
Keyword(s):  
Image Enhancement ◽  
Local Contrast ◽  
Fusion Method ◽  
Formation Model ◽  
Low Contrast ◽  
White Balance ◽  
Multi Scale ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method

In this study, an underwater image enhancement method based on local contrast correction (LCC) and multi-scale fusion is proposed to resolve low contrast and color distortion of underwater images. First, the original image is compensated using the red channel, and the compensated image is processed with a white balance. Second, LCC and image sharpening are carried out to generate two different image versions. Finally, the local contrast corrected images are fused with sharpened images by the multi-scale fusion method. The results show that the proposed method can be applied to water degradation images in different environments without resorting to an image formation model. It can effectively solve color distortion, low contrast, and unobvious details of underwater images.

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