• Journal of the Institute of Convergence Signal Processing
• /
• v.8 no.4
• /
• pp.249-254
• /
• 2007

This paper describes a technique for detecting the boundary of the optic disk in digital image of the retina using inward and outward curve evolution. Optic disk boundary offers medical information about glaucoma progresses. For accurate boundary detection, image inpainting based on PDE removes blood vessels crossing the optic disk. For removing noises and preserving boundary of optic disk in image inpainting process, the anisotropic diffusion filtering is developed. After pre-processing, the optic disk boundary is determined using inward and outward curve evolution. Experimental results show that blurring effect of original region and optic disk boundary is reduced considerably. By the proposed method, we can detect correct disk boundary compare to conventional method.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.12
• /
• pp.2337-2342
• /
• 2008

In this paper, we propose the novel approach to enhance the visual quality of the digital image with adaptively sharpening and removing the noise. Image enhancement is performed in two ways. The pixels in the high dynamics area are sharpened by the adaptive unsharp mask with the parameter, which is derived using the statistical information of the image. On the other hand, the proposed algorithm do not perform the sharpening process in the uniform area that may cause the undesired artifact due to noise amplification, rather it performs smoothing to suppress the noise in this area. The decision, which process will be applied at the pixel, is also controlled by the statistics of the pixel dynamics. The proposed algorithm enhances the visual quality almost automatically by sharpening and smoothing at the same time with less parameter selection.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.6
• /
• pp.675-681
• /
• 2019

Noise removal is a pre-requisite procedure in image processing, and various methods have been studied depending on the type of noise and the environment of the image. However, for image processing with high-frequency components, conventional additive white Gaussian noise (AWGN) removal techniques are rather lacking in performance because of the blurring phenomenon induced thereby. In this paper, we propose an algorithm to minimize the blurring in AWGN removal processes. The proposed algorithm sets the high-frequency and the low-frequency component filters, respectively, depending on the pixel properties in the mask, consequently calculating the output of each filter with the addition or subtraction of the input image to the reference. The final output image is obtained by adding the weighted data calculated using the standard deviations and the Gaussian distribution with the output of the two filters. The proposed algorithm shows improved AWGN removal performance compared to the existing method, which was verified by simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.428-430
• /
• 2022

Image processing is playing an important part in automation and artificial intelligence systems, such as object tracking, object recognition and classification, and the importance of IoT technology and automation is emphasizing as interest in automation increases. However, in a system that requires detailed data such as an image boundary, a precise noise removal algorithm is required. Therefore, in this paper, we propose a filtering algorithm based on the pixel value distribution pattern to minimize the information loss in the filtering process. The proposed algorithm finds the distribution pattern of neighboring pixel values with respect to the pixel values of the input image. Then, a weight mask is calculated based on the distribution pattern, and the final output is calculated by applying it to the filtering mask. The proposed algorithm has superior noise removal characteristics compared to the existing method and restored the image while minimizing blurring.

• The Journal of Korean Society for Radiation Therapy
• /
• v.35
• /
• pp.41-51
• /
• 2023

Purpose: This study compares and analyzes the image quality of 3D-CBCT(Cone Beam Computed-Tomography) and Gated CBCT according to baseline changes during SBRT(Stereotactic Body RadioTherapy) in lung cancer patients to find a useful CBCT method for correcting movement due to breathing Materials and methods : Insert a solid tumor material with a diameter of 3 cm into the QUASAR^TM phantom. 4-Dimentional Computed-Tomography(4DCT) images were taken with a speed of the phantom at period 3 sec and a maximum amplitude of 20 mm. Using the contouring menu of the computerized treatment planning system Eclipse^TM Gross Tumor Volume was outlined on solid tumor material. Set-up the same as when acquiring a 4DCT image using Truebeam STx^TM, breathing patterns with baseline changes of 1 mm, 3 mm, and 5 mm were input into the phantom to obtain 3D-CBCT (Spotlight, Full) and Gated-CBCT (Spotlight, Full) images five times repeatedly. The acquired images were compared with the Signal-to-Noise Ratio(SNR), Contrast-to-Noise Ratio(CNR), Tumor Volume Length, and Motion Blurring Ratio(MBR) based on the 4DCT image. Results: The average Signal-to-Noise Ratio, Contrast-to-Noise Ratio, Tumor Volume Length and Motion Blurring Ratio of Spotlight Gated CBCT images were 13.30±0.10%, 7.78±0.16%, 3.55±0.17%, 1.18±0.06%. As a result, Spotlight Gated-CBCT images according to baseline change showed better values than Spotligtht 3D-CBCT images. Also, the average Signal-to-Noise Ratio, Contrast-to-Noise Ratio, Tumor Volume Length and Motion Blurring Ratio of Full Gated CBCT images were 12.80±0.11%, 7.60±0.11%, 3.54±0.16%, 1.18±0.05%. As a result Full GatedCBCT images according to baseline change showed better values than Full 3D-CBCT images. Conclusion : Compared to 3D-CBCT images, Gated-CBCT images had better image quality according to the baseline change, and the effect of Motion Blurring Artifacts caused by breathing was small. Therefore, it is considered useful to image guided using Gated-CBCT when a baseline change occurs due to difficulty in regular breathing during SBRT that exposes high doses in a short period of time

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2019.11a
• /
• pp.210-212
• /
• 2019

본 논문에서는 CNN을 이용하여 전방위 영상에 대해 워터마크를 추출하는 방법을 제안한다. 네트워크의 입력은 전방위 영상에서 SIFT 특징점을 기준으로 잘라낸 영역들이며, 네트워크를 통해 전방위 영상 생성 과정에서의 왜곡을 보정하고 워터마크를 분류한다. 또한 네트워크의 훈련 집합에는 원본 영상 외에 JPEG 압축, 가우시안 노이즈, 가우시안 블러링, 샤프닝 공격을 가한 영상들도 포함시켜서 학습을 통해 공격에 대한 강인성을 가지도록 한다. 이에 대해 훈련된 네트워크로 추출한 워터마크와 알고리즘으로 추출한 워터마크를 비교하여 제안하는 방법의 유효성을 확인한다.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.723-726
• /
• 2001

일반적으로 블록기반의 동영상 압축방식은 블록킹효과를 필연적으로 수반한다. 특히 저비트율의 동영상에서는 블록킹 효과가 다른 어떤 영상의 왜곡보다 많이 발생한다. 본 논문에서는 이러한 블록킹효과를 효율적으로 인간 시각체계에 적합하게 실시간으로 제거하는 후처리 알고리즘을 제안한다. 우선 복원된 영상에서 인간의 시각체계와 동영상의 특성에 따라 3가지의 모드로 분리하여 QP(quantization Parameter)에 따라 임계치를 변화함으로써 각 모드의 필터링 범위를 가변시켰다. 이후에 각 모드에 알맞은 일차원 및 적응형 필터링을 적용한다. 적용된 모드별 필터링은 과도한 블러링 현상을 방지하고 영상내의 실제 에지성분읓 보호하면서 효과적으로 블록킹효과를 제거한다. 본 논문에서 제안하는 알고리즘을 실험 영상에 적용하였을 경우에 주관적 화질 및 객관적 화질인 PSNR로 0.5dB 정도 향상되었다.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1998.06c
• /
• pp.439-443
• /
• 1998

본 연구에서는 50% Tukey 창함수를 이용하여 위너필터를 설계하고 표면결함의 영상을 개선하였다. 이 위너필터는 높은 공간주파수 성분에 대해 낮은 잡음이득을 주며 안정된 필터 동작 특성을 보였다. 실험을 위하여 쿼드러춰 방식의 초음파현미경을 구성하고 시편으로 10원주화를 사용하였다. 실험결과 개선된 영상은 블러링 효과가 제거되어 우수한 영상 화질을 나타내었다.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
• /
• 2006.06a
• /
• pp.119-122
• /
• 2006

홍채인식 시스템의 성능은 입력된 눈 영상으로부터 정확한 홍채 영역의 검출 및 효율적인 홍채코드의 생성 등의 영향을 받으나, 이를 위해서는 입력된 눈 영상에서 홍채 패턴이 선명해야 한다는 선행 조건이 존재한다. 초점이 맞지 않아 흐리게 나온 영상 눈을 감은 영상, 속눈썹에 의해 홍채영역이 가려진 영상, 움직임에 의해 블러링된 영상, 또는 홍채가 아닌 속눈썹 등의 다른 부분에 초점이 맞춰진 영상 등에서는 선명한 홍채 패턴을 얻을 수 없으므로 전체 인식 성능을 떨어뜨리는 요인이 된다. 그러므로 이러한 영상들을 자동으로 걸러내 제거해주는 눈 영상 화질 측정 방법이 필요하다. 본 논문에서는 눈 영상의 초점이 잘 맞는지 측정하는 방법을 제안하고 자체적으로 획득한 데이터베이스를 이용해 이를 테스트하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.6
• /
• pp.155-161
• /
• 2009

Any classification process using SAR images presupposes the reduction of multiplicative speckle noise, since the variations caused by speckle make it extremely difficult to distinguish between neighboring classes within the feature space. This paper focus an argument of effective filter for preserving the weak boundaries by using the proposed method. To reduce speckle noise without blurring the edges of reconstructed image use wavelet-based sigma filter. As a result, the edge information of reconstructed image reduce blurring. Simulation results show that proposed method gives a better subjective quality than conventional methods for the speckle noise.