A New Adaptive Threshold Image-Denoising Method Based on Edge Detection

2014 ◽  
Vol 678 ◽  
pp. 137-142 ◽  
Author(s):  
Yuan Jiao ◽  
Bin Wen Huang
Keyword(s):  
Edge Detection ◽  
Wavelet Packet ◽  
Adaptive Threshold ◽  
Difficult Problem ◽  
Denoising Method ◽  
Dependency Relation ◽  
Estimate Method ◽  
Edge Detection Method ◽  
Image Edges ◽  
Orthogonal Wavelet Transform

In image processing, removal of noise without blurring the image edges is a difficult problem. Aiming at orthogonal wavelet transform and traditional threshold’s shortage, a new wavelet packet transform adaptive threshold image de-noising method which is based on edge detection is proposed. By edge detection method, the wavelet packet coefficients corresponding to edge which is detected and other non-edge wavelet packet coefficients are treated by different threshold. Using the relativity among wavelet packet coefficients and neighbor dependency relation, at the same time, adopting the new variance neighbor estimate method and then the adaptive threshold is produced. From the experiment result, we see that compared with traditional methods, this method can not only effectively eliminate noise, but can also well keep original image’s information and the quality after image de-noising is very well.

A New Adaptive Image Denoising Method Based on Wavelet Packet Transform and Neighbor Dependency

2013 ◽  
Vol 433-435 ◽  
pp. 301-305
Author(s):  
Bin Wen Huang ◽  
Yuan Jiao
Keyword(s):  
High Frequency ◽  
Wavelet Packet ◽  
Estimation Method ◽  
Low Frequency ◽  
Adaptive Threshold ◽  
Difficult Problem ◽  
Wavelet Packet Transform ◽  
Denoising Method ◽  
Image Edges ◽  
Orthogonal Wavelet Transform

In image processing, removal of noise without blurring the image edges is a difficult problem. Aiming at orthogonal wavelet transform and traditional thresholds shortage, a new adaptive threshold image de-noising method which is based on wavelet packet transform and neighbor dependency is proposed. Low frequency part and high frequency part can be decomposed at the same time in wavelet packet transform and the information contained in wavelet coefficients is redundant. Using this kind of relativity in wavelet packet coefficients, we use a new variance neighbor estimation method and then neighbor dependency adaptive threshold is produced. From the experiment result, we see that compared with traditional methods, this method can not only effectively eliminate noise, but can also well keep original images information and the quality after image de-noising is very well.

A Novel Approach of Edge Detection Based on Vector Morphology

2014 ◽  
Vol 511-512 ◽  
pp. 545-549
Author(s):  
Qiang Chen
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Color Image ◽  
Detection Algorithm ◽  
Difficult Problem ◽  
Color Images ◽  
Edge Detection Algorithm ◽  
Morphological Gradient ◽  
Novel Approach ◽  
Image Edges

Edge detection of color image is a difficult problem in image processing. Although a lot of corresponding to methods have been proposed, however, none of them can effectively detect image edges while suppressing noises. In this paper, a novel edge detection algorithm of color images based on mathematical morphology is proposed. Through designing a new anti-noise morphological gradient operators, we can obtain better edge detection results. The proposed gradient operators are applied to detect edge for three components of a color image. An then, the final edge can be obtained by fusing the three edge results. Experimental results show that the feasibility and effectiveness of the proposed algorithm. Moreover, the proposed algorithm has better effect of preserving the edge details and better robustness to noises than traditional methods.

A New Method of Denoising by Reserving Edges for SAR Image

2013 ◽  
Vol 291-294 ◽  
pp. 2859-2862
Author(s):  
Lian Fei Duan ◽  
Chuan Ting Wei ◽  
Jing Wang ◽  
Yuan Wen Dai
Keyword(s):  
Edge Detection ◽  
New Method ◽  
Sar Image ◽  
Detection Experiment ◽  
Denoising Method ◽  
Image Edge Detection ◽  
Image Edge ◽  
Image Blur ◽  
Image Edges

Aimed at the problem of image blur while denoising in SAR image, a new denoising method by reserving edges based on MSP-ROA operator is presented after analyzing the image edge detection. The SAR image edges are well reserved while denoising for combining denoising with the edge detection. Experiment results show that the method is feasible and effective.

Image Edge Detection Based on Direction Fuzzy Entropy

2011 ◽  
Vol 268-270 ◽  
pp. 1234-1238
Author(s):  
Xian Qing Ling ◽  
Jun Lu ◽  
Lei Wang
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Feature Space ◽  
Fuzzy Entropy ◽  
Noise Performance ◽  
Edge Pixel ◽  
Image Edge Detection ◽  
Image Edge ◽  
Edge Detection Method ◽  
Image Edges

To improve the ability of the fuzzy edge detection and anti-noise performance, the paper proposes a new weighted direction fuzzy entropy image edge detection method. The proposed method converts the feature space of image gray to the fuzzy feature space, and then extracts the weighted information measure of the direction structural in the fuzzy entropy feature space. Finally, the proposed method determines the edge pixel by an adaptive threshold after non-maxima suppression. The experiment demonstrates that the proposed method can extract the image edges effectively by means of the fuzzy edge detection.

Macrozooplankton Image Edge Detection Using Wavelet Packet Decomposition

2010 ◽  
Vol 108-111 ◽  
pp. 44-49
Author(s):  
Jing Ying Zhao ◽  
Hai Guo ◽  
Xing Bin Sun
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Wavelet Packet ◽  
Detection Methods ◽  
Automatic Identification ◽  
Wavelet Packet Decomposition ◽  
Edge Detectors ◽  
Reconstruction Image ◽  
Image Edge ◽  
Edge Detection Method

Comparing with the phytoplankton, there are few researches on zooplanktons. Now, many waterworks don’t monitor the zooplanktons in source water. There isn’t effective detection method for several common macro zooplanktons such as chironomid larvae, cyclops and so on, and little has been done in the field of the macro zooplanktons automatic identification and monitor. This paper puts for forward a macrozooplankton edge detection method based on wavelet packet decomposition and reconstruction. We erase the high frequency parts by applying wavelet packet decomposition in the original images and then detect the edge of reconstruction images using the common edge detectors such as Prewitt, Sobel, Roberts, Laplacian of Gaussion, Canny and so on. The experimental results show that the edge detection methods in the reconstruction image work better than in the original image.

Detection of Diabetic Retinopathy Using Sobel edge detection method in DIP

2012 ◽  
Vol 3 (7) ◽  
pp. 1-4
Author(s):  
Jyoti Patil ◽  
Dr. A. L. Chaudhari
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Edge Detection ◽  
Automated Analysis ◽  
Detection Algorithm ◽  
Sobel Edge Detection ◽  
Edge Detection Method ◽  
Image Edges ◽  
Processing Techniques ◽  
Automated Image Processing

Diabetic retinopathy, a complication of diabetes that occurs as a result of vascular changes in the retina, It is a major cause of loss of vision. Automated image processing has the potential to assist in the early detection of diabetes, by detecting changes in blood vessel patterns in the retina. Image processing techniques can reduce the work of ophthalmologists and the tools used automatically locate the exudates. 0In this paper the process and knowledge of Digital Image Processing (DIP) is used. Automated analysis techniques for retinal images have been an important area of research for developing screening programmers. By using MATLAB for programming to develop the DIP tool for diagnosis of eye infection . Sobel edge detection algorithm is a method to find the edge pixels in an image. Edges are pixels which carry important information in an image. Thus sobel method is best technique for features are extended & used to classify the pixels in the patch into vessel and non vessel

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