• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.275-278
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• 2002

Sharpness enhancement, which strengthen the edge(high frequency) of image, is widely studied for image processing research area. In this paper, psychophysical experiment is conducted by the 20 observers with simple linear unsharp masking for sharpness enhancement. The experimental results extracted using z-score analysis and linear regression suggests observer preferable sharpness enhancement method for digital television.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1692-1695
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• 2007

We describe the image enhancement method of applying two spatial filters with different characteristics adaptively. An adaptive method is introduced so that sharpness enhancement is performed only in regions where the image exhibits significant dynamics, while noise reduction is achieved in smooth regions. Simulation results show that the proposed method improved the image quality.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.110-117
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• 2014

This paper reports a depth-adaptive sharpness adjustment algorithm for stereoscopic perception improvement, and presents its field-programmable gate array (FPGA) implementation results. The first step of the proposed algorithm was to estimate the depth information of an input stereo video on a block basis. Second, the objects in the input video were segmented according to their depths. Third, the sharpness of the foreground objects was enhanced and that of the background was maintained or weakened. This paper proposes a new sharpness enhancement algorithm to suppress visually annoying artifacts, such as jagging and halos. The simulation results show that the proposed algorithm can improve stereoscopic perception without intentional depth adjustments. In addition, the hardware architecture of the proposed algorithm was designed and implemented on a general-purpose FPGA board. Real-time processing for full high-definition stereo videos was accomplished using 30,278 look-up tables, 24,553 registers, and 1,794,297 bits of memory at an operating frequency of 200MHz.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.32-39
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• 2012

This paper develops a robust image enhancement method by adjusting image signal energy according to the direction and the variation of image signal in DCT domain. To accomplish this, we measure the gradient of image signal directly in DCT domain and then adjust frequency components involved in sharpness, local contrast and global contrast using the direction and the magnitude of the measured gradient The experiment showed that the proposed method produces the best quality of an image without causing blocking, ringing artifacts and boosting noise.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.1
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• pp.8-14
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• 2007

X-ray digital tomosynthesis is widely used in the nondestructive testing and evaluation, especially for the printed circuit boards (PCBs). In this study, we propose a simple method to reduce the blur artefact, frequently claimed in the conventional digital tomosynthesis based on SAA (shift-and-add) algorithm, and thus restore the image sharpness. The proposed method is basically based on the SAA, but has a correction procedure by finding blur artefacts from the forward-and back-projection for the firstly obtained, manipulated backprojection data. The manipulation is the replacement of the original data at the POI (plane-of-interest) by zeros. This method has been compared with the conventional SAA algorithm using the experimental measurements and Monte Carlo simulation for the designed PCB phantom. The comparison showed a much enhancement of sharpness in the images obtained from the proposed method.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.32-40
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• 2022

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.144-154
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• 2013

This paper proposes a new super-resolution algorithm where sharpness enhancement is merged in order to improve overall visual quality of up-scaled images. In the learning stage, multiple dictionaries are generated according to sharpness strength, and a proper dictionary among those dictionaries is selected to adapt to each patch in the inference stage. Also, additional post-processing suppresses boosting of artifacts in input low-resolution images during the inference stage. Experimental results that the proposed algorithm provides 0.3 higher CPBD than the bi-cubic and 0.1 higher CPBD than Song's and Fan's algorithms. Also, we can observe that the proposed algorithm shows better quality in textures and edges than the previous works. Finally, the proposed algorithm has a merit in terms of computational complexity because it requires the memory of only 17% in comparison with the previous work.

• Journal of Information Technology Applications and Management
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• v.30 no.1
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• pp.11-19
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• 2023

To remove unnecessary background from tooth X-ray images and enhance the sharpness of tooth and gum images, image processing techniques including contrast adjustment and histogram equalization are used. The introduction of two methods for detecting the boundary of the tooth and gum region and separating the tooth and gum from the background. In both cases, the background of the tooth X-ray images could be removed as a result, improving the quality of the images. The proposed method improves MTF (Modulation Transfer Function), an image performance indicator, as a result of measuring MTF. The original image's spatial frequency ranged from 4.73 to 11.40 lp/mm at the 10% response, whereas the proposed image's spatial frequency ranged from 10.90 to 11.85 lp/mm, giving uniformly enhanced results. In contrast, tooth and gums could not be completely separated from the background using Apple's Lift subject from background function.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.84-91
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• 2016

Most recently, the technology of around view monitoring(AVM) system or the security systems could provide users with images by using a fisheye lens. The filmed images through fisheye lens have an advantage of providing a wider range of scenes. On the other hand, filming through fisheye lens also has disadvantages of distorting images. Especially, it causes the sharpness of images to degrade because the edge of images is out of focus. The influence of a blur still remains at the end of the range when the super-resolution techniques is applied in order to enhance the sharpness. It degrades the clarity of high resolution images and occurs artifacts, which leads to deterioration in the performance of super-resolution algorithm. Therefore, in this paper we propose self-similarity-based pre-processing method to improve the sharpness at the edge. Additionally, we implement the acceleration in the GPU environment of entire algorithm and verify the acceleration.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.108-116
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• 2018

In this paper, we propose an image enhancement method based on Multi-Scale Retinex theory that designs Unsharp Masking Filter (UMF) and emphasizes the contrast ratio adaptively. Unsharp Masking (UM) technique emphasizes image sharpness and improves contrast ratio by adding high frequency component to the original image. The high frequency component is obtained by differentiating between original image and low frequency image. In this paper, we present how to design an UMF kernel and to adaptively apply it to increase the contrast ratio according to multi-scale retinex theory which resembles human visual system. Experimental results show that the proposed method has better quantitative performance indexes such as PSNR, ambe & SSIM and better qualitative feature like halo artifact suppression.