• KIPS Transactions on Software and Data Engineering
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• v.3 no.6
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• pp.231-236
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• 2014

The transit time of contrast agents and the parameters of time-intensity curves in ultrasonography are important factors to diagnose various diseases of a digestive organ. We have implemented an automatic parametric imaging method to overcome the difficulty of the diagnosis by naked eyes. However, the micro-bubble noise and the respiratory motions may degrade the reliability of the parameter images. In this paper, we introduce an optimization technique based on MRF(Markov Random Field) model to enhance the quality of the parameter images, and present an image tracking algorithm to compensate the image distortion by respiratory motions. A method to extract the respiration periods from the ultrasound image sequence has been developed. We have implemented the ROI(Region of Interest) tracking algorithm using the dynamic weights and a momentum factor based on these periods. An energy function is defined for the Gibbs sampler of the image enhancement method. Through the experiments using the data to diagnose liver lesions, we have shown that the proposed method improves the quality of the parametric images.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.725-737
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• 2021

Although the performance of cameras is gradually improving now, there are noise in the acquired digital images from the camera, which acts as an obstacle to obtaining high-resolution images. Traditionally, a filtering method has been used for denoising, and a convolutional neural network (CNN), one of the deep learning techniques, has been showing better performance than traditional methods in the field of image denoising, but the details in images could be lost during the learning process. In this paper, we present a CNN for image denoising, which improves image details by learning the details of the image based on wavelet transform. The proposed network uses two subnetworks for detail enhancement and noise extraction. The experiment was conducted through Gaussian noise and real-world noise, we confirmed that our proposed method was able to solve the detail loss problem more effectively than conventional algorithms, and we verified that both objective quality evaluation and subjective quality comparison showed excellent results.

• Journal of KIISE:Software and Applications
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• v.37 no.7
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• pp.573-577
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• 2010

Image resolution improvement is commonly technique for applications such as image reconstruction or enlargement. It is important to remove image quality degradation such as blocking effect or artificiality occurrence. In this paper, we propose image resolution improvement method using loss information of image. The proposed compute and estimate by low level interpolation of obtained low resolution image, it is applied by interpolated high resolution as 1-stage interpolation. We generate last interpolation image by iteration of error computation and application between obtained low resolution image and 1-stage interpolation image. By experiments using same test images, we confirmed improvement over 3.2dB of average PSNR and enhancement of subject image quality. Also, we can reduce more than 85% computation complexity. The proposed image resolution improvement method may be helpful for various applications of image processing.

• Journal of Korea Multimedia Society
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• v.16 no.8
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• pp.934-942
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• 2013

Image scaling is used for a variety of real-life applications. In order to evaluate the performance of transform functions, the image quality are compared together before and after processing. For the objective evaluation of the transform functions, the exact criterion of image quality is required, and various aspects approaches are practically performed. However, few researches have been conducted on image quality measurement considering the position of pixels that are skipped or newly generated in the process of the image scaling. Therefore this paper focuses on the objective image quality measurement for positions of skipped or estimated pixels in the image scaling. The proposed method generated new image quality measure considering the positional changes using a conventional measure and evaluated sensitivity about positional changes. Through this experiments, it is observed that conventional image quality measurement is definitely affected by positional changes of a skipped and estimated pixels. It is also confirmed that the proposed method is an objective criterion to represent image quality for positional changes of skipped or estimated pixels. The proposed method can be used as a criterion to evaluate the performance of image restoration or enhancement functions.

• Korean Journal of Digital Imaging in Medicine
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• v.16 no.2
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• pp.25-29
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• 2014

The full-field digital mammography (FFDM), which has been known as a digital breast imaging system, carries out more outstanding performance than the screen-film mammography in overall image quality, skin & nipple, description of pectoral muscle and expression of micro-calcification. Thus, in this thesis, I perform experiments for both the enhancement of image quality and accurate estimation of the result in question, when detecting the very tiny-sized lesions in mammography. The image of digital breast X-rays is the important diagnostic tool for detecting early breast cancer and micro calcification lesion. The experiment of how much compression rate has an effect on the result of diagnosis in the case of microcalcification lesion, with JPEG2000 40:1 compression and over 50% enlargement led to obscure or definitely unacceptable diagnostic results is performed. And in another study of assessment of PSNR degree. I recognized the importance of standardized management system in mammography, where not to mention the accurate reading of the image has the most crucial role in diagnosis

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.1066-1071
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• 1998

This paper aims to examine the relationship between the directional characteristics and the quality for fingerprint image as preprocessing stage for adative image enchancement. In order to do that, we transformed the original images into directional images and set up the subimage size of 16, 32, 64 and the direction of 1, 2, 3, 4. Then we extracted the accumulated directional value as the measurement of quality for fingerprint images. By using the clustering algirthm, we performed an analytic experiemnt with the result. Finally, we could extract the optimal subimage size and directional characteristics of fingerprint image.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.51-60
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• 2024

Aiming at the problem of low contrast and difficult to recognize video images in low-light environment, we propose an adaptive contrast compensation enhancement algorithm based on human visual perception. First of all, the video image characteristic factors in low-light environment are extracted: AL (average luminance), ABWF (average bandwidth factor), and the mathematical model of human visual CRC(contrast resolution compensation) is established according to the difference of the original image's grayscale/chromaticity level, and the proportion of the three primary colors of the true color is compensated by the integral, respectively. Then, when the degree of compensation is lower than the bright vision precisely distinguishable difference, the compensation threshold is set to linearly compensate the bright vision to the full bandwidth. Finally, the automatic optimization model of the compensation ratio coefficient is established by combining the subjective image quality evaluation and the image characteristic factor. The experimental test results show that the video image adaptive enhancement algorithm has good enhancement effect, good real-time performance, can effectively mine the dark vision information, and can be widely used in different scenes.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.829-830
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• 2008

In modern days, many of the images are captured by using various devices, such as PDA, digital camera, or cell phone camera. Because all these devise have a limited dynamic range, images captured in real world scenes with high dynamic ranges usually exhibit poor visibility and low contrast, which may make important image features lost or hard to tell by human viewers. In this paper, the efficient color image enhancement method is presented. Experimental result show that the proposed method yields better performance of color enhancement over the previous work for test color images.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.371-372
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• 2007

In this paper, we propose the color image enhancement method to improve the quality of color image without producing over-saturation and color contour artifacts. The proposed method has two manners, which one is the adaptive cumulative density function and the other is the luminance-based saturation extension. That is focused on a preference color processing in order to generate better image qualify than the algorithms focused on a uniform one for human vision.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1681-1685
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• 2014

The visual quality of medical image is an important factor for diagnosis accuracy. Therefore, the methods to improve the quality of medical image have studied. Among them, frequency domain filter is very powerful method to impove the visual quality of image. In this paper, the X-ray medical image using optimized high-pass filter was improved edges. The result image was improved edge and contrast of flat area using optimized high frequency emphasis filter. At last, the result image is to minimize the noise using the minimum mean square error(MMSE) filter. As a result, the proposed method has enhanced contrast and edge of the image in the contrast of existing filters, with the noise canceling effect.