Guided Intra-Patch Smoothing Graph Filtering for Single-Image Denoising

A Block-Grouping Method for Image Denoising by Block Matching and 3-D Transform Filtering

Image denoising by block matching and threedimensionaltransform filtering (BM3D) is a two steps state-ofthe-art algorithm that uses the redundancy of similar blocks innoisy image for removing noise. Similar blocks which can havesome overlap are found by a block matching method and groupedto make 3-D blocks for 3-D transform filtering. In this paper wepropose a new block grouping algorithm in th...

Guided Image Filtering for Image Enhancement

Noise removing belongs to image restoration in digital image processing. It’s the essential guarantee of identifying image information and the reliable guarantee of making further image processing. A satisfying result can’t be found if processing method such as feature extraction, registration or image fusion is carried out on an image with noise. So removing noise is absolutely necessary for i...

Digital Image Watermarking Based On Gradient Direction Quantization and Denoising Using Guided Image Filtering

ABTRACT Digital watermarking is the art of hiding of information or data in documents, where the embedded information or data can be extracted to resist copyright violation or to verify the uniqueness of a document which leads to security. Protecting the digital content has become a major issue for content owners and service providers. Watermarking using gradient direction quantization is based...

Statistical and Adaptive Patch-based Image Denoising

Alternating guided image filtering

Edge preserving filters aim to simplify the representation of images (e.g., by reducing noise or eliminating irrelevant detail) while preserving their most significant edges. These filters are typically nonlinear and locally smooth the image structure while minimizing both blurring and over-sharpening of visually important edges. Here we present the Alternating Guided Filter (AGF) that achieves...