Applied-Information Technology with Method of Digital Image Noise Processing

2014 ◽  
Vol 951 ◽  
pp. 253-256 ◽  
Author(s):  
Guo Qing Yu ◽  
Chen Meng Sui ◽  
Bing Dong Sui
Keyword(s):  
Image Processing ◽  
Information Technology ◽  
Digital Image Processing ◽  
Digital Image ◽  
Average Method ◽  
Image Noise ◽  
Computer Algorithm ◽  
Basic Knowledge ◽  
Median Filtering ◽  
Low Pass

Digital image processing is a kind of technology which employs a certain algorithm to realize image processing through computer algorithm. The powerful capacity of computing and graphics displaying function of Matlab makes image processing becomes more simple and intuitive. This paper introduces the basic knowledge of dealing with noise in digital image, expounds the neighborhood average method, median filtering in detail, and low pass filtering and other typical of eliminating noise method , and at the same time analyzes and compares the characteristics of several typical methods by use of the software Matlab.

Realization of Car’s Frontal Projected Area Based on OpenCV

2013 ◽  
Vol 300-301 ◽  
pp. 1673-1676 ◽  
Author(s):  
Chun Bo Dong ◽  
Xing Jun Hu ◽  
Yan Wang ◽  
Li Min Fu
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
High Accuracy ◽  
Median Filtering ◽  
Contour Extraction ◽  
Projected Area ◽  
Automotive Body ◽  
Body Development ◽  
Image Processing Algorithms

Digital image processing technology applied to the field of automotive body development, especially the aerodynamic development of the external shape of automobile. This method and its corresponding software improve the efficiency compared with other traditional fluid software tools in processing the car’s front area, reduce artificial error, and have high accuracy. Digital image processing algorithms used in this article includes Image Gray, Median Filtering, Image Segmentation, Contour Extraction and so on.

Comparative Analysis on Noise Processing of Image

2013 ◽  
Vol 718-720 ◽  
pp. 2159-2162
Author(s):  
Hua Jun Dong ◽  
Xue Mei Jiang ◽  
Chen Xu Niu
Keyword(s):  
Image Processing ◽  
Comparative Analysis ◽  
Digital Image Processing ◽  
Digital Image ◽  
Median Filter ◽  
Wiener Filter ◽  
Image Noise ◽  
Two Dimensional ◽  
Wavelet Filter ◽  
Average Filter

The existence of noises have great interference on image processing, so the elimination of image noise is of great importance. In this paper, based on the digital image processing, the methods of average filter, wiener filter, median filter, two-dimensional wavelet filter, maximum and minimum filter are used to eliminate the salt & pepper noise of image. Then we analysis and compare the results of the five methods to find the best way to eliminate the image noise.

Computer Digital Image Processing Application and Research

2014 ◽  
Vol 926-930 ◽  
pp. 3389-3392 ◽  
Author(s):  
Hong Peng Yang
Keyword(s):  
Image Processing ◽  
Information Technology ◽  
Digital Image Processing ◽  
Digital Image ◽  
Present Situation ◽  
Communication Management ◽  
Processing Application ◽  
Image Information ◽  
Image Processing Application ◽  
Characteristics Of Image

This paper Based on the analysis of the characteristics of image information and image information technology, analyzes some field demand for image information technology, analyzed the image application of news communication management, Analysis of domestic and foreign research present situation, proposed to increase the image signal, research ideas application depth and the breadth of color and its technology in the field , to accelerate the process of social normalization.

scholarly journals Application of Different Filtering Techniques in Digital Image Processing

2021 ◽  
Vol 2062 (1) ◽  
pp. 012007
Author(s):  
Sumant Sekhar Mohanty ◽  
Sushreeta Tripathy
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Noise ◽  
Noise Model ◽  
Electronic Noise ◽  
Original Image ◽  
Color Information ◽  
Processing Steps ◽  
Filtering Techniques

Abstract Noise in an image is a random variation of brightness or color information in the original image. Noise is consistently presented in digital images during picture obtaining, coding, transmission, and processing steps. Image noise is most apparent in image regions with a low signal level. There are various reasons for the creation of noise in an image, such as electronic noise in amplifiers or detectors, disturbances and overheating of the sensor, disturbances in the medium of traveling for a digital image, etc. Noise is exceptionally hard to eliminate from the digital pictures without the earlier information of the noise model. There are various types of noise that can be available in a noise model. Filters are used to remove these types of noises in a digital image in image processing. In this research, we have implemented different filtering techniques that have been used to remove the noises in an image.

The Digital Method of Clothing Extension Measurement

2011 ◽  
Vol 175-176 ◽  
pp. 807-810
Author(s):  
Zhi Ge Chen ◽  
Qing Guan Chen
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Noise ◽  
Digital Method ◽  
Stripe Width ◽  
Fabric Strength ◽  
The Relationship

Fabric extension can be measured by using fabric strength tester in laboratory. But the extension is difficult to be measured when the clothing is in wearing. In this paper, the relationship between the extension of clothing and the fabric tension was discussed according to the experiment result. The digital image processing will be used to grab clothing images and to measure the extension of fabric. The techniques of digital image processing, such as binary conversion of image, noise points deleting, smooth processing of stripe edge and the stripe width measuring, were applied in this research. Based on experiment results, the relation between the fabric tension and extension were linear when the clothing was under the condition of small strength.

An Automatic Microalgal Cells Counting Method

2014 ◽  
Vol 1010-1012 ◽  
pp. 178-181
Author(s):  
Yun Zhao ◽  
De Jian Zheng ◽  
Ying Shen
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Binary Image ◽  
Morphological Operations ◽  
Microscopic Image ◽  
Median Filtering ◽  
Counting Method ◽  
Automatic Counting

An automatic counting method for microalgal cells were proposed using digital image processing with characteristics of microalgae microscopic image considered. Firstly, the microalgae image was pretreated with graying, and was then applied the median filtering to remove the noise. Secondly, the image was applied Bot-hat conversion to enhance the contrast. Thirdly, the image was segmented with Otsu algorithm, and was then applied morphological operations. Finally, the binary image segments representing microalgal cells were labeled and counted. The results of experiments showed that this method was simple, efficient and accurate in counting microalgal cells in the microscopic image.

An Overview of Digital Image Processing and Recognition (Invited Paper)

1982 ◽  
Vol 40 ◽  
pp. 700-702
Author(s):  
R. C. Gonzalez
Keyword(s):  
Image Processing ◽  
New York ◽  
Digital Image Processing ◽  
Digital Image ◽  
Practical Implementation ◽  
Submarine Cable ◽  
Vigorous Growth ◽  
Digitized Pictures ◽  
Processing Techniques ◽  
And Storage

Interest in digital image processing techniques dates back to the early 1920's, when digitized pictures of world news events were first transmitted by submarine cable between New York and London. Applications of digital image processing concepts, however, did not become widespread until the middle 1960's, when third-generation digital computers began to offer the speed and storage capabilities required for practical implementation of image processing algorithms. Since then, this area has experienced vigorous growth, having been a subject of interdisciplinary research in fields ranging from engineering and computer science to biology, chemistry, and medicine.

A method to measure pores and fissures in geologic materials under S.E.M. by digital image processing

1978 ◽  
Vol 36 (1) ◽  
pp. 212-213
Author(s):  
L. Montoto ◽  
M. Montoto ◽  
A. Bel-Lan
Keyword(s):  
Image Processing ◽  
Optical Microscopy ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Processing ◽  
Free Surfaces ◽  
Geologic Materials ◽  
Automatic Information ◽  
Detector Output ◽  
Rock Specimens

INTRODUCTION.- The physical properties of rock masses are greatly influenced by their internal discontinuities, like pores and fissures. So, these need to be measured as a basis for interpretation. To avoid the basic difficulties of measurement under optical microscopy and analogic image systems, the authors use S.E.M. and multiband digital image processing. In S.E.M., analog signal processing has been used to further image enhancement (1), but automatic information extraction can be achieved by simple digital processing of S.E.M. images (2). The use of multiband image would overcome difficulties such as artifacts introduced by the relative positions of sample and detector or the typicals encountered in optical microscopy.DIGITAL IMAGE PROCESSING.- The studied rock specimens were in the form of flat deformation-free surfaces observed under a Phillips SEM model 500. The SEM detector output signal was recorded in picture form in b&w negatives and digitized using a Perkin Elmer 1010 MP flat microdensitometer.

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