• Title/Summary/Keyword: Anisotropic Filtering

Search Result 29, Processing Time 0.023 seconds

Nonlinear Anisotropic Filtering with Considering of Various Structures in Magnetic Resonance Imaging (자기공명영상에서 다양한 구조들을 고려한 비선형 이방성 필터링)

  • Song Young-Chul
    • The Transactions of the Korean Institute of Electrical Engineers D
    • /
    • v.52 no.3
    • /
    • pp.148-155
    • /
    • 2003
  • In this paper, a nonlinear anisotropic filtering method without the loss of important information happened due to the repeated filtering in magnetic resonance images is proposed. First of all original images are divided into four regions, e.g., SPR(Strong Plain Region), EPR(Easy Plain Region), SER(Strong Edge Region), and EER(Easy Edge Region). An optimal template among multiple templates is selected, then the nonlinear anisotropic filtering based on the template is applied in pixel by pixel basis. In the proposed algorithm, filtering strength of EER containing important information is adjusted very weak and filtering strength for remaining regions is also adjusted according to the degree of the importance. In spite of repeated filtering, resulting images by the proposed method could still preserve anatomy information of original images without any degradation. Compared to the existing nonlinear anisotropic filtering, the proposed filtering method with multiple templates provides higher reliability for filtered images.

ENHANCEMENT AND SMOOTHING OF HYPERSPECTAL REMOTE SENSING DATA BY ADVANCED SCALE-SPACE FILTERING

  • Konstantinos, Karantzalos;Demetre, Argialas
    • Proceedings of the KSRS Conference
    • /
    • v.2
    • /
    • pp.736-739
    • /
    • 2006
  • While hyperspectral data are very rich in information, their processing poses several challenges such as computational requirements, noise removal and relevant information extraction. In this paper, the application of advanced scale-space filtering to selected hyperspectral bands was investigated. In particular, a pre-processing tool, consisting of anisotropic diffusion and morphological leveling filtering, has been developed, aiming to an edge-preserving smoothing and simplification of hyperspectral data, procedures which are of fundamental importance during feature extraction and object detection. Two scale space parameters define the extent of image smoothing (anisotropic diffusion iterations) and image simplification (scale of morphological levelings). Experimental results demonstrated the effectiveness of the developed scale space filtering for the enhancement and smoothing of hyperspectral remote sensing data and their advantage against watershed over-segmentation problems and edge detection.

  • PDF

Segmentation of Neuronal Axons in Brainbow Images

  • Kim, Tae-Yun;Kang, Mi-Sun;Kim, Myoung-Hee;Choi, Heung-Kook
    • Journal of Korea Multimedia Society
    • /
    • v.15 no.12
    • /
    • pp.1417-1429
    • /
    • 2012
  • In neuroscientific research, image segmentation is one of the most important processes. The morphology of axons plays an important role for researchers seeking to understand axonal functions and connectivity. In this study, we evaluated the level set segmentation method for neuronal axons in a Brainbow confocal microscopy image. We first obtained a reconstructed image on an x-z plane. Then, for preprocessing, we also applied two methods: anisotropic diffusion filtering and bilateral filtering. Finally, we performed image segmentation using the level set method with three different approaches. The accuracy of segmentation for each case was evaluated in diverse ways. In our experiment, the combination of bilateral filtering with the level set method provided the best result. Consequently, we confirmed reasonable results with our approach; we believe that our method has great potential if successfully combined with other research findings.

Detection of the Optic Disk Boundary in Retinal Images Using Inward and Outward Curve Evolution (양방향 곡선 전개 방식을 이용한 망막영상에서의 시신경 원판 경계 검출)

  • Lee Sang-Kwan;Kim Seong-Kon
    • The Journal of the Korea Contents Association
    • /
    • v.5 no.6
    • /
    • pp.138-145
    • /
    • 2005
  • 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. This paper offers medical information about glaucoma progresses. For accurate boundary detection, image inpainting based on texture synthesis 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 necessary. After pre-processing, the optic disk boundary is determined using inward and outward curve evolution. The experimental results show that the algorithm is effective for detection of optic disk boundary.

  • PDF

A Study on Shape Registration Using Level-Set Model and Surface Registration Volume Rendering of 3-D Images (레밸 세트 모텔을 이용한 형태 추출과 3차원 영상의 표면 정합 볼륨 렌더링에 관한 연구)

  • 김태형;염동훈;주동현;김두영
    • Journal of the Institute of Convergence Signal Processing
    • /
    • v.3 no.4
    • /
    • pp.29-34
    • /
    • 2002
  • In this paper, we present a new geometric active contour model based on level set methods introduced by Osher and Sethian for detection of object boundaries or shape and we adopt anisotropic diffusion filtering method for removing noise from original image. In order to minimize the processing time, we use the narrow band method which allows us to perform calculations in the neighborhood of the contour and not in the whole image. Using anisotropic diffusion filtering for each slice, we have the result with reduced noise and extracted exact shape. Volume rendering operates on three-dimensional data, processes it, and transforms it into a simple two-dimensional image.

  • PDF

Three-Dimensional Face Point Cloud Smoothing Based on Modified Anisotropic Diffusion Method

  • Wibowo, Suryo Adhi;Kim, Sungshin
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • v.14 no.2
    • /
    • pp.84-90
    • /
    • 2014
  • This paper presents the results of three-dimensional face point cloud smoothing based on a modified anisotropic diffusion method. The focus of this research was to obtain a 3D face point cloud with a smooth texture and number of vertices equal to the number of vertices input during the smoothing process. Different from other methods, such as using a template D face model, modified anisotropic diffusion only uses basic concepts of convolution and filtering which do not require a complex process. In this research, we used 6D point cloud face data where the first 3D point cloud contained data pertaining to noisy x-, y-, and z-coordinate information, and the other 3D point cloud contained data regarding the red, green, and blue pixel layers as an input system. We used vertex selection to modify the original anisotropic diffusion. The results show that our method has improved performance relative to the original anisotropic diffusion method.

Image enhancement using the local statistics

  • Ryu, Jin-Bong;Kim, Woon-Kyung
    • Proceedings of the IEEK Conference
    • /
    • 2003.11a
    • /
    • pp.3-6
    • /
    • 2003
  • A nonlinear iterative filtering based on local statistics and anisotropic diffusion is introduced. Local statistics determines the diffusion coefficient at each iteration step. Anisotropic diffusion can be seen as estimates a piecewise smooth image from the noisy input image in the experimental section, our results are shown to suppress noise with preserving the edges. Therefore, it enhances the image and improves performance.

  • PDF

Detection of the Optic Disk Boundary in Retinal Images using Image inpainting based on PDE (PDE 기반의 이미지 인페인팅을 이용한 시신경 원판 경계 검출에 관한 연구)

  • Kim, Tae-Hyoung;Kim, Seng-Hyen;Kim, Jin-Man;Gong, Jae-Woong;Kim, Doo-Young
    • 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.

  • PDF

Image Quality Improvement in Computed Tomography by Using Anisotropic 2-Dimensional Diffusion Based Filter (비등방성 2차원 확산 기반 필터를 이용한 전산화단층영상 품질 개선)

  • Seoung, Youl-Hun
    • Journal of the Korean Society of Radiology
    • /
    • v.10 no.1
    • /
    • pp.45-51
    • /
    • 2016
  • The purpose of this study was tried to remove the noise and improve the spatial resolution in the computed tomography (CT) by using anisotropic 2-dimensional (2D) diffusion based filter. We used 4-channel multi-detector CT and american association of physicists in medicine (AAPM) phantom was used for CT performance evaluation to evaluate the image quality. X-ray irradiation conditions for image acquisition was fixed at 120 kVp, 100 mAs and scanned 10 mm axis with ultra-high resolution. The improvement of anisotropic 2D diffusion filtering that we suggested firstly, increase the contrast of the image by using histogram stretching to the original image for 0.4%, and multiplying the individual pixels by 1.2 weight value, and applying the anisotropic diffusion filtering. As a result, we could distinguished five holes until 0.75 mm in the original image but, five holes until 0.40 mm in the image with improved anisotropic diffusion filter. The noise of the original image was 46.0, the noise of the image with improved anisotropic 2D diffusion filter was decreased to 33.5(27.2%). In conclusion improved anisotropic 2D diffusion filter that we proposed could remove the noise of the CT image and improve the spatial resolution.

A Hippocampus Segmentation in Brain MR Images using Level-Set Method (레벨 셋 방법을 이용한 뇌 MR 영상에서 해마영역 분할)

  • Lee, Young-Seung;Choi, Heung-Kook
    • Journal of Korea Multimedia Society
    • /
    • v.15 no.9
    • /
    • pp.1075-1085
    • /
    • 2012
  • In clinical research using medical images, the image segmentation is one of the most important processes. Especially, the hippocampal atrophy is helpful for the clinical Alzheimer diagnosis as a specific marker of the progress of Alzheimer. In order to measure hippocampus volume exactly, segmentation of the hippocampus is essential. However, the hippocampus has some features like relatively low contrast, low signal-to-noise ratio, discreted boundary in MRI images, and these features make it difficult to segment hippocampus. To solve this problem, firstly, We selected region of interest from an experiment image, subtracted a original image from the negative image of the original image, enhanced contrast, and applied anisotropic diffusion filtering and gaussian filtering as preprocessing. Finally, We performed an image segmentation using two level set methods. Through a variety of approaches for the validation of proposed hippocampus segmentation method, We confirmed that our proposed method improved the rate and accuracy of the segmentation. Consequently, the proposed method is suitable for segmentation of the area which has similar features with the hippocampus. We believe that our method has great potential if successfully combined with other research findings.