• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.179.1-179
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• 2001

Successive image contrast enhancement was used to direct digital radiography system. This system was accurately required acquisition signal in each pixel. But, applied high electric field in a-Se thin film for x-ray conversion layer was caused to acquisition signal distortion, then bring low image contrast. The purpose of this study was to reduce the signal distortion, carried out different electrode size.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.2
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• pp.24-29
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• 2014

Digital mammography is the most common technique for the early detection of breast cancer. To diagnose the breast cancer in early stages and treat efficiently, many image enhancement methods have been developed. This paper presents a multi-scale contrast enhancement method in the Laplacian pyramid for the digital mammogram. The proposed method decomposes the image into the contrast measures by the Gaussian and Laplacian pyramid, and the pyramid coefficients of decomposed multi-resolution image are defined as the frequency limited local contrast measures by the ratio of high frequency components and low frequency components. The decomposed pyramid coefficients are modified by the contrast measure for enhancing the contrast, and the final enhanced image is obtained by the composition process of the pyramid using the modified coefficients. The proposed method is compared with other existing methods, and demonstrated to have quantitatively good performance in the contrast measure algorithm.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.951-958
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• 2021

Objective: To evaluate the usefulness of virtual monochromatic images (VMIs) obtained using dual-layer dual-energy CT (DL-DECT) for evaluating brain tumors. Materials and Methods: This retrospective study included 32 patients with brain tumors who had undergone non-contrast head CT using DL-DECT. Among them, 15 had glioblastoma (GBM), 7 had malignant lymphoma, 5 had high-grade glioma other than GBM, 3 had low-grade glioma, and 2 had metastatic tumors. Conventional polychromatic images and VMIs (40-200 keV at 10 keV intervals) were generated. We compared CT attenuation, image noise, contrast, and contrast-to-noise ratio (CNR) between tumor and white matter (WM) or grey matter (GM) between VMIs showing the highest CNR (optimized VMI) and conventional CT images using the paired t test. Two radiologists subjectively assessed the contrast, margin, noise, artifact, and diagnostic confidence of optimized VMIs and conventional images on a 4-point scale. Results: The image noise of VMIs at all energy levels tested was significantly lower than that of conventional CT images (p < 0.05). The 40-keV VMIs yielded the best CNR. Furthermore, both contrast and CNR between the tumor and WM were significantly higher in the 40 keV images than in the conventional CT images (p < 0.001); however, the contrast and CNR between tumor and GM were not significantly different (p = 0.47 and p = 0.31, respectively). The subjective scores assigned to contrast, margin, and diagnostic confidence were significantly higher for 40 keV images than for conventional CT images (p < 0.01). Conclusion: In head CT for patients with brain tumors, compared with conventional CT images, 40 keV VMIs from DL-DECT yielded superior tumor contrast and diagnostic confidence, especially for brain tumors located in the WM.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1269-1274
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• 2014

In computer vision research, binarization procedure is one of the most frequently used tools to discriminate target objects from background in grey level binary image. Fuzzy binarization is a reliable technique in environment with high uncertainty such as medical image analysis by setting the threshold as the average of minimum and maximum brightness with triangle type fuzzy membership function. However, this technique is also known as contrast sensitive method thus its discrimination power is not so great when the image has low contrast difference between objects and backgrounds and suffer from information loss as a result. Thus, in this paper, we propose a fuzzy binarization using ART2 algorithm to handle such low contrast image analysis. Proposed ART2 algorithm is applied to determine the medium point of membership function in the fuzzy binarization paradigm. The proposed methods shows low information loss rate in our experiment.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.39-47
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• 2016

In this paper, we propose an approach for real time computation of rayleigh CLAHE using a FPGA. The contrast enhancement technique should be applied in thermal equipment having a low contrast image. And thermal equipment must be processed in real time. The CLAHE is an improved algorithm based Histogram Equalization, but the HW design is complex. A value greater than a given threshold in CLAHE should be equally distributed on the other histogram bin, this process requires iterations for the distribution. But implementation of this processing in the FPGA is constrained, so this section was implemented on the assumption of the histogram distribution or modified the operation process or implemented separately in the CPU. In this paper, we designed a distinct redistribution operation in two stages. So FPGA was designed for easy, this was designed to be distributed evenly without the assumptions and constraints. In addition, we have designed a CLAHE with the rayleigh distribution to the FPGA. The simulation shows that the proposed method provides a better image quality in the thermal image.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.651-661
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• 2008

This paper proposes a novel contrast enhancement (CE) algorithm for color images using the modified error diffusion (ED). After conventional color histogram equalization (HE), artifacts such as false contours are produced in the contrast enhanced image. The proposed CE algorithm using the modified ED consists of two parts: CE and ED. In the first part, a low-contrast input image is enhanced by the conventional HE method. In the second part, we use the modified ED algorithm. The inputs of the second part are the average and scaled difference images of the original color input image and the HE image, in which the scaled color difference image is diffused by the ED algorithm. In the proposed algorithm, the modified ED algorithm reduces the artifacts produced in the HE image, and increases the number of color levels. Computer simulations with a number of low-contrast color images show the effectiveness of the proposed CE method in terms of the visual quality as well as the probability mass function. It can be used as a post-processing for CE with simultaneous artifact reduction in various display devices.

• Journal of the Korean Home Economics Association
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• v.35 no.2
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• pp.159-172
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• 1997

The purpose of this study was to investigate visual evaluation according to various methods of motif presentation and the value contrast between the motif and background. The instruments developed for this purpose were two sets of stimuli and a response scale. the first set consisted of pattern stimuli. they were eight photographs of floral patterns constructed by using six different motif presentation methods and two different value contrasts. The second set had eight clothing stimuli, photographs of clothings with the above floral patterns. The 7-point sementic differential scale of 19 bipolar adjectives was used as the response scale. The data was analyzed by factor analysis, ANOVA and T-test. The major findings from this study were as follows; 1. Four factors emerged to account for the dimensional structure of the floral pattern image. These factors were attractiveness, tenderness, attention, and maturity. among them attractiveness and tenderness were the major dimensions 2. The patterns and the clothings had no significant difference from each other in terms of attractiveness and tenderness, but in terms of maturity and attention. The pattern presented a cute and sober image, but the clothing presented mature and gorgeous image. 3. methods of motif presentation had significant effects on all the factors. The pattern by shading method gave the most attractive and soft image, the one by line the most soberest, the one by area the most gorgeous, the one by collage the most unattractive, hardest, and cutest, and the one by mosaics the maturest. 4. The value contrast between the motif and background had no significant effects on attractiveness and maturity, but on tenderness and attention. The patterns with a high valued background presented a soft image, but the one with a low valued background a hard image. The patterns with a low valued area presented gorgeous image.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.27-33
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• 2018

In this paper, we propose an efficient edge preserving smoothing filter for Infrared image that can reduce noise while preserving edge information. Infrared images suffer from low signal-to-noise ratio, low edge detail information and low contrast. So, detail enhancement and noise reduction play crucial roles in infrared image processing. We first apply a guided image filter as a local analysis. After the filtering process, we optimization globally using relativity of guided image filter. Our method outperforms the previous methods in removing the noise while preserving edge information and detail enhancement.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1004-1019
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• 2021

To solve the problems of the low image contrast, fuzzy edge details and edge details missing in noisy image fusion, this study proposes a noisy infrared and visible light image fusion algorithm based on non-subsample contourlet transform (NSCT) and an improved bilateral filter, which uses NSCT to decompose an image into a low-frequency component and high-frequency component. High-frequency noise and edge information are mainly distributed in the high-frequency component, and the improved bilateral filtering method is used to process the high-frequency component of two images, filtering the noise of the images and calculating the image detail of the infrared image's high-frequency component. It can extract the edge details of the infrared image and visible image as much as possible by superimposing the high-frequency component of infrared image and visible image. At the same time, edge information is enhanced and the visual effect is clearer. For the fusion rule of low-frequency coefficient, the local area standard variance coefficient method is adopted. At last, we decompose the high- and low-frequency coefficient to obtain the fusion image according to the inverse transformation of NSCT. The fusion results show that the edge, contour, texture and other details are maintained and enhanced while the noise is filtered, and the fusion image with a clear edge is obtained. The algorithm could better filter noise and obtain clear fused images in noisy infrared and visible light image fusion.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.126-136
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• 2007

This paper presents an enhanced algorithm for compensating the visual quality in back-light image. Current cameras do not represent all details of scene into human's eye. Saturation and underexposure are common problems in back-light image. Retinex algorithm, derived from Land's theory on human visual perception is known to be effective in enhancing the contrast. However, its weaknesses are long processing time and low contrast of bright area in back-light scene because of compensating the details of dark area. In this paper, K-Retinex algorithm is proposed to reduce the processing time and enhance the contrast in both dark and bright area. To show the superiority of proposed algorithm, we compare the processing time, local standard deviation and contrast per pixel of each area above.