Image Compression with Anisotropic Diffusion
نویسندگان
چکیده
منابع مشابه
Three-Dimensional Data Compression with Anisotropic Diffusion
In 2-D image compression, recent approaches based on image inpainting with edge-enhancing anisotropic diffusion (EED) rival the transform-based quasi-standards JPEG and JPEG 2000 and are even able to surpass it. In this paper, we extend successful concepts from these 2-D methods to the 3-D setting, thereby establishing the first PDE-based 3-D image compression algorithm. This codec uses a cuboi...
متن کاملImage Compression with Anisotropic Geodesic Triangulations
We propose a new image compression method based on geodesic Delaunay triangulations. Triangulations are generated by a progressive geodesic meshing algorithm which exploits the anisotropy of images through a farthest point sampling strategy. This seeding is performed according to anisotropic geodesic distances which force the anisotropic Delaunay triangles to follow the geometry of the image. G...
متن کاملImage Denoising Using Anisotropic Diffusion Equations on Reflection and illumination Components of Image
This paper proposes a new hybrid method based on Homomorphic filtering and anisotropicdiffusion equations for image denoising. In this method, the Homomorphic filtering extracts the reflectionand illumination components of a noisy image. Then a suitable image denoising method based onanisotropic diffusion is applied to each components with its special user-defined parameters .This hybridscheme ...
متن کاملAnisotropic diffusion in image processing
The cover image shows a thresholded nonwoven fabric image which was processed by applying a coherence-enhancing anisotropic diffusion filter (see Section 5.2 for more details). The goal was to visualize the quality relevant adjacent fibre structures , so-called stripes. The displayed equations describe the basic structure of nonlinear diffusion filtering in the continuous, semidiscrete, and ful...
متن کاملImage Statistics and Anisotropic Diffusion
Many sensing techniques and image processing applications are characterized by noisy, or corrupted, image data. Anisotropic diffusion is a popular, and theoretically well understood, technique for denoising such images. Diffusion approaches however require the selection of an “edge stopping” function, the definition of which is typically ad hoc. We exploit and extend recent work on the statisti...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Mathematical Imaging and Vision
سال: 2008
ISSN: 0924-9907,1573-7683
DOI: 10.1007/s10851-008-0087-0