Image Compression with Anisotropic Diffusion
Journal of Mathematical Imaging and Vision
Beating the Quality of JPEG 2000 with Anisotropic Diffusion
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Low Frequency Domain Aided Texture Synthesis for Intra Prediction
AMT '09 Proceedings of the 5th International Conference on Active Media Technology
A Learning-Based Framework for Low Bit-Rate Image and Video Coding
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Bit-rate and computational complexity scalability design for texture-synthesis based video coding
Proceedings of the First International Conference on Internet Multimedia Computing and Service
Image compression with downsampling and overlapped transform at low bit rates
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Component-based image coding using non-local means filtering and an autoregressive texture model
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Block-based image compression with parameter-assistant inpainting
IEEE Transactions on Image Processing
Edge-based compression of cartoon-like images with homogeneous diffusion
Pattern Recognition
Inpainting with image patches for compression
Journal of Visual Communication and Image Representation
Color correction and compression for multi-view video using h.264 features
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Simultaneous inpainting for image structure and texture using anisotropic heat transfer model
Multimedia Tools and Applications
A novel customized recompression framework for massive internet images
CVM'12 Proceedings of the First international conference on Computational Visual Media
An efficient framework for image/video inpainting
Image Communication
Hi-index | 0.00 |
In this paper, image compression utilizing visual redundancy is investigated. Inspired by recent advancements in image inpainting techniques, we propose an image compression framework towards visual quality rather than pixel-wise fidelity. In this framework, an original image is analyzed at the encoder side so that portions of the image are intentionally and automatically skipped. Instead, some information is extracted from these skipped regions and delivered to the decoder as assistant information in the compressed fashion. The delivered assistant information plays a key role in the proposed framework because it guides image inpainting to accurately restore these regions at the decoder side. Moreover, to fully take advantage of the assistant information, a compression-oriented edge-based inpainting algorithm is proposed for image restoration, integrating pixel-wise structure propagation and patch-wise texture synthesis. We also construct a practical system to verify the effectiveness of the compression approach in which edge map serves as assistant information and the edge extraction and region removal approaches are developed accordingly. Evaluations have been made in comparison with baseline JPEG and standard MPEG-4 AVC/H.264 intra-picture coding. Experimental results show that our system achieves up to 44% and 33% bits-savings, respectively, at similar visual quality levels. Our proposed framework is a promising exploration towards future image and video compression.