• Current Optics and Photonics
• /
• v.2 no.1
• /
• pp.101-106
• /
• 2018

Color-normal observers (CNOs) and color-deficient observers (CDOs) have different preferences and emotions for color images. A color-image quality-enhancement algorithm for a CDO is developed to easily adjust images according to each observer's preference or image quality factors. The color-perception differences between CDO and CNO are analyzed and modeled in terms of the YCbCr chroma ratio and hue difference; then the color-shift method is designed to control the degree of color difference.

• Journal of Biomedical Engineering Research
• /
• v.17 no.4
• /
• pp.427-432
• /
• 1996

The primary purpose of port filming is to verify the treatment volume under treatment. Although the image quality with the megavoltage x-ray beam is poorer than with the diagnostic or the simulator film. This paper proposes an edge-adaptive Kalman filter for the image enhancement of port films. Suggested filtering procedure preserves edge information and eliminates edge noise and inside and outside treatment area preserving treatment boundary.

• Journal of Korea Multimedia Society
• /
• v.19 no.2
• /
• pp.233-239
• /
• 2016

Color enhancement basically deals with color manipulation in digital images. Recently, the technique has become widely used as a result of the increasing use of digital cameras. Retinex-based colorenhancement algorithms are a popular technique. In this paper, retinex with bilateral filtering is proposed to improve the quality of poorly illuminated images. Generally, it consists of three main steps: first, a retinex-based algorithm with color restoration; second, transformation mapping using histogram matching; and finally, smoothing the image using a bilateral filter. The experimental results demonstrate that the proposed method can successfully enhance image contrast while avoiding the halo effect and maintaining the color distribution in the image.

• 한국방재학회:학술대회논문집
• /
• 2011.02a
• /
• pp.39-39
• /
• 2011

This study presents an effective vision-based system for cable bridge damage detection. In theory, cable bridges need to be inspected the outer as well as the inner part. Starting from August 2010, a new research project supported by Korea Ministry of Land, Transportation Maritime Affairs(MLTM) was initiated focusing on the damage detection of cable system. In this study, only the surface damage detection algorithm based on a vision-based system will be focused on, an overview of the vision-based cable damage detection is given in Fig. 1. Basically, the algorithm combines the image enhancement technique with principal component analysis(PCA) to detect damage on cable surfaces. In more detail, the input image from a camera is processed with image enhancement technique to improve image quality, and then it is projected into PCA sub-space. Finally, the Mahalanobis square distance is used for pattern recognition. The algorithm was verified through laboratory tests on three types of cable surface. The algorithm gave very good results, and the next step of this study is to implement the algorithm for real cable bridges.

• Journal of Broadcast Engineering
• /
• v.24 no.2
• /
• pp.292-298
• /
• 2019

In this paper, we show how to provide high quality image service using cloud server and image quality enhancement algorithm. In other words, based on the concept of ViVa (Video Value Addition) proposed in the paper, we propose an improved system compared to the existing streaming service by providing a high-quality video with the transmission bit rate and calculation amount necessary to serve low-quality images.

• Journal of KIISE:Software and Applications
• /
• v.31 no.7
• /
• pp.911-921
• /
• 2004

Accurate minutiae extraction from input fingerprint images is one of the critical modules in robust automatic fingerprint identification system. However, the performance of a minutiae extraction is heavily dependent on the quality of the input fingerprint images. If the preprocessing is performed according to the fingerprint image characteristics in the image enhancement step, the system performance will be more robust. In this paper, we propose a knowledge-based preprocessing method, which extracts S features (the mean and variance of gray values, block directional difference, orientation change level, and ridge-valley thickness ratio) from the fingerprint images and analyzes image quality with Ward's clustering algorithm, and enhances the images with respect to oily/neutral/dry characteristics. Experimental results using NIST DB 4 and Inha University DB show that clustering algorithm distinguishes the image Quality characteristics well. In addition, the performance of the proposed method is assessed using quality index and block directional difference. The results indicate that the proposed method improves both the quality index and block directional difference.

• Progress in Medical Physics
• /
• v.19 no.3
• /
• pp.143-149
• /
• 2008

The aim of this study is to suggest the method for image enhancement of digital chest radiograph and evaluate clinically the quality of the resultant image. A nonlinear iterative filter was developed in order to reduce quantum noise preserving edge. Dynamic range was adjusted and adaptive image enhancement was performed based on the property of anatomic region and the degree of compatibility with neighboring pixels. The lung fields were enhanced appropriately to visualize effectively vascular tissue, bronchus and lung tissue with the desired mediastinum enhancement. Clinic evaluation was performed by three radiologists with at least 8 years experience. The anatomic regions of 11 in PA and 9 in Lateral were observed carefully in each 100 radiographs according to ITU (International Telecommunication Union) recommendation 500 protocol. The result showed the mean 3.4 between good and adequate. This means that the clinical utility of the image quality is enough. In this study, image enhancement was carried out considering image display device and human perceptual system to prevent the loss of useful anatomic information. In order to increase the diagnostic accuracy in digital radiograph, the continuous study on image enhancement is needed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.9
• /
• pp.2626-2641
• /
• 2024

Images taken in low lamination condition suffer from low contrast and loss of information. Low lumination image enhancement algorithms are required to improve the quality and broaden the applications of such images. In this study, we proposed a new Low lumination image enhancement architecture consisting of a transformer-based curve learning and an encoder-decoder-based texture enhancer. Considering the high effectiveness of curve matching, we constructed a transformer-based network to estimate the learnable curve for pixel mapping. Curve estimation requires global relationships that can be extracted through the transformer framework. To further improve the texture detail, we introduced an encoder-decoder network to extract local features and suppress the noise. Experiments on LOL and SID datasets showed that the proposed method not only has competitive performance compared to state-of-the-art techniques but also has great efficiency.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.3
• /
• pp.1233-1243
• /
• 2015

The contrast enhancement is great challenge in the image processing when images are suffering from poor contrast problem. Therefore, in order to overcome this problem an automatic method is proposed for contrast enhancement of natural color images. The proposed method consist of two stages: in first stage lightness component in YIQ color space is normalized by sigmoid function after the adaptive histogram equalization is applied on Y component and in second stage automatic color contrast enhancement algorithm is applied on output of the first stage. The proposed algorithm is tested on different NASA color images, hyperspectral color images and other types of natural color images. The performance of proposed algorithm is evaluated and compared with the other existing contrast enhancement algorithms in terms of colorfulness metric and color enhancement factor. The higher values of colorfulness metric and color enhancement factor imply that the visual quality of the enhanced image is good. Simulation results demonstrate that proposed algorithm provides higher values of colorfulness metric and color enhancement factor as compared to other existing contrast enhancement algorithms. The proposed algorithm also provides better visual enhancement results as compared with the other existing contrast enhancement algorithms.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.7
• /
• pp.36-41
• /
• 2018

An image intensifying device is equipment that makes weak objects visible in a dark environment, such as making nighttime bright enough to let objects be visually observed. It is possible to obtain a clear image by amplifying the light in the presence of a certain amount of weak light. However, in an extremely low-light environment, where even moonlight is not present, there is not enough light to amplify anything, and the sharpness of the screen deteriorates. In this paper, a method is proposed to improve image quality by using multiple filters and anisotropic diffusion for output noise of the image-intensifying device in extreme low-light environments. For the experiment, the output of the image-intensifying device was obtained under extremely low-light conditions, and signal processing for improving the image quality was performed. The configuration of the filters for signal processing uses anisotropic diffusion after applying a median filter and a Wiener filter for effective removal of salt-and-pepper noise and Gaussian noise, which constitute the main noise appearing in the image. Experimental results show that the improvement visually enhanced image quality. Both peak signal-to-noise ratio (PSNR) and SSIM, which are quantitative indicators, show improved values.