• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2002년도 봄 학술발표논문집 Vol.29 No.1 (B)
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• pp.109-111
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• 2002

Visual organs play an important role in human information recognition processes. If they are expressed in a way of digital information, it makes much bigger amount of visual information among any other information. For that reason, MPEG-2 has been taken use of to represent information compressing technology in multi-media. Although the imported data would basically contain noises, when original video images are encoded into MPET-2. Accordingly, we propose soft- $\alpha$ filter to improve image quality of digital image received from the actual image and to reduce noises from them. We also propose a method combining vertical/horizontal filter and soft- $\alpha$ filter on MPEG-2 video image. We can get two kinds of effects from the advantages of this kind of combination. Firstly, it will reduce processing time ducting horizontal and vetical filtering process. It will cover time for soft- $\alpha$ filter. Secondly, it will simplify the colors in horizontal and vertical filter. Therefore we can get clearer quality without noises from soft- $\alpha$ filter.

• 디지털산업정보학회논문지
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• 제8권3호
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• pp.41-48
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• 2012

In this paper, we propose a method of edge detection for noisy image. The proposed method uses a progressive filter for noise reduction and a Sobel operator for edge detection. The progressive filter combines a median filter and a modified rational filter. The proposed method for noise reduction adjusts rational filter direction according to an edge in the image which is obtained by median filtering. Our method effectively attenuates the noise while preserving the image details. Edge detection is performed by a Sobel operator. This operator can be implemented by integer operation and is therefore relatively fast. Our proposed method not only preserves edge, but also reduces noise in uniform region. Thus, edge detection is well performed. Our proposed method could improve results using further developed Sobel operator. Experimental results show that our proposed method has better edge detection with correct positions than those by existing median and rational filtering methods for noisy image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.3092-3107
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• 2019

Visible-infrared image fusion is a process of synthesizing an infrared image and a visible image into a fused image. This process synthesizes the complementary advantages of both images. The infrared image is able to capture a target object in dark or foggy environments. However, the utility of the infrared image is hindered by the blurry appearance of objects. On the other hand, the visible image clearly shows an object under normal lighting conditions, but it is not ideal in dark or foggy environments. In this paper, we propose a multi-guided filter and a real-time image fusion method. The proposed multi-guided filter is a modification of the guided filter for multiple guidance images. Using this filter, we propose a real-time image fusion method. The speed of the proposed fusion method is much faster than that of conventional image fusion methods. In an experiment, we compare the proposed method and the conventional methods in terms of quantity, quality, fusing speed, and flickering artifacts. The proposed method synthesizes 57.93 frames per second for an image size of $320{\times}270$. Based on our experiments, we confirmed that the proposed method is able to perform real-time processing. In addition, the proposed method synthesizes flicker-free video.

• 한국멀티미디어학회논문지
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• 제17권8호
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• pp.923-936
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• 2014

Images can be contaminated with different types of noise, for different reasons. The neighborhood averaging and smoothing by image averaging are the classical image processing techniques for noise removal. The classical spatial filtering refers to the aggregate of pixels composing an image and operating directly on these pixels. To reduce or remove effectively noise in image sequences, it usually needs to use noise reduction filter based on space or time domain such as method of spatial or temporal filter. However, the method of spatial filter can generally cause that signals of objects as the target are also blurred. In this paper, we propose temporal filter using the piece-wise quadratic function model and enhancement algorithm of image quality for the performance improvement of target detection and tracking by heterogeneous noise reduction. Image tracking simulation that utilizes real IIR(Imaging Infra-Red) images is employed to evaluate the performance of the proposed image processing algorithm.

• 한국방사선학회논문지
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• 제11권2호
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• pp.69-77
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• 2017

본 연구는 영상의 노이즈 감소를 위한 복합필터 제안과 간 초음파영상에서 노이즈 제거를 통한 영상품질의 향상으로 정확한 영상 해석에 도움을 주고자 하였다. 실험은 ATS-539 다목적용 초음파팬텀을 이용하여 Gaussian blurring filter, Sharpening filter, Median filter의 조합으로 상위 7개의 복합필터를 선정하고 이를 간 초음파영상에 적용하였다. 그 결과 상위 7개 복합필터 적용하였을 때 SNR, CNR, MSR 값이 모두 증가하는 것으로 나타났다. 이 중 복합필터 1과 2가 가장 높은 값을 나타내었다. 또한 PSNR 30 dB이상, SSIM 1에 가까운 결과값을 나타내어 영상의 손실률이 적음을 알 수 있었다. 따라서 본 연구에서 제안한 복합필터의 적절한 적용은 정확한 영상의 판독과 해석에 도움을 줄 수 있을 것이다.

• Journal of information and communication convergence engineering
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• 제13권4호
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• pp.264-269
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• 2015

The chest X-ray image cannot be focused in the same manner that optical lenses are and the resultant image generally tends to be slightly blurred. Therefore, the methods to improve the quality of chest X-ray image have been studied. In this paper, the inherent noises of the input images are suppressed by adding the Laplacian image to the original. First, the chest X-ray image using an Gaussian high pass filter and an optimal high frequency emphasis filter has shown improvements in the edges and contrast of flat areas. Second, using fuzzy logic_histogram equalization, each pixel of the chest X-ray image shows the normal distribution of intensities that are not overexposed. As a result, the proposed method has shown the enhanced edge and contrast of the images with the noise canceling effect.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권8호
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• pp.360-367
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• 2002

In this paper, genetic algorithm based adaptive image enhancement filtering scheme is proposed and Implemented on FPGA board. Conventional filtering methods require a priori noise information for image enhancement. In general, if a priori information of noise is not available, heuristic intuition or time consuming recursive calculations are required for image enhancement. Contrary to the conventional filtering methods, the proposed filter system can find optimal combination of filters as well as their sequent order and parameter values adaptively to unknown noise types using structured genetic algorithms. The proposed image enhancement filter system is mainly composed of two blocks. The first block consists of genetic algorithm part and fitness evaluation part. And the second block consists of four types of filters. The first block (genetic algorithms and fitness evaluation blocks) is implemented on host computer using C code, and the second block is implemented on re-configurabe FPGA board. For gray scale control, smoothing and deblurring, four types of filters(median filter, histogram equalization filter, local enhancement filter, and 2D FIR filter) are implemented on FPGA. For evaluation, three types of noises are used and experimental results show that the Proposed scheme can generate optimal set of filters adaptively without a pioi noise information.

• Journal of Information Processing Systems
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• 제12권4호
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• pp.631-643
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• 2016

Due to the block-based discrete cosine transform (BDCT), JPEG compressed images usually exhibit blocking artifacts. When the bit rates are very low, blocking artifacts will seriously affect the image's visual quality. A bilateral filter has the features for edge-preserving when it smooths images, so we propose an adaptive-weighted bilateral filter based on the features. In this paper, an image-deblocking scheme using this kind of adaptive-weighted bilateral filter is proposed to remove and reduce blocking artifacts. Two parameters of the proposed adaptive-weighted bilateral filter are adaptive-weighted so that it can avoid over-blurring unsmooth regions while eliminating blocking artifacts in smooth regions. This is achieved in two aspects: by using local entropy to control the level of filtering of each single pixel point within the image, and by using an improved blind image quality assessment (BIQA) to control the strength of filtering different images whose blocking artifacts are different. It is proved by our experimental results that our proposed image-deblocking scheme provides good performance on eliminating blocking artifacts and can avoid the over-blurring of unsmooth regions.

• 한국정보통신학회논문지
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• 제18권7호
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• pp.1681-1685
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• 2014

의료영상의 화질이 진단의 정확성에 중요한 요소이다. 그러므로 의료영상의 화질을 향상시킬 수 있는 방법들이 연구되어져 왔다. 그 중에서 주파수 도메인 필터가 영상의 화질을 향상시킬 수 있는 강력한 도구이다. 본 논문에서는 X선 의료영상에 기존의 고주파통과 필터에 최적값을 적용해서 에지영역을 개선하였고, 결과영상에 기존의 고주파 강조 필터에 최적값을 사용하여 에지영역 및 평탄영역의 대비를 향상시켰다. 마지막으로, 최소평균제곱오차필터를 사용해서 결과영상에 잡음을 최소화했다. 결과적으로, 제안된 방법이 기존 필터들에 비해서 영상의 대비와 에지부분들을 향상시켰으며, 더불어 잡음제거의 효과를 보였다.

• 디지털산업정보학회논문지
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• 제11권4호
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• pp.155-164
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• 2015

In this paper, we propose a new color interpolation method based on trilateral filter approach, which not only preserve the high-frequency components(image edge) while interpolating the missing raw data of color image(bayer data pattern), but also immune to the image noise components and better preserve the detail of the low-frequency components. The method is the trilateral filter approach applying a gradient to the low frequency components of the image signal in order to preserve the high-frequency components and the detail of the low-frequency components through the measure of the freedom of similarity among adjacent pixels. And also we perform Gaussian smoothing to the interpolated image data in order to robust to the noise. In this paper, we compare the conventional demosaicing algorithm and the proposed algorithm using 10 test images in terms of hue MAD, saturation MAD and CPSNR for the objective evaluation, and verify the performance of the proposed algorithm.