STRUCTURE AND TEXTURE SYNTHESIS

An approach for filling-in blocks of missing data in wireless image transmission is presented in this paper. When compression algorithms such as JPEG are used as part of the wireless transmission process, images are first tiled into blocks of 8x8 pixels. When such images are transmitted over fading channels, the effects of noise can destroy entire blocks of the image. Instead of using common retransmission query protocols, we aim to reconstruct the lost data using correlation between the lost block and its neighbours. If the lost block contained structure, it is reconstructed using an image inpainting algorithm, while texture synthesis is used for the textured blocks. The switch between the two schemes is done in a fully automatic fashion based on the surrounding available blocks. The performance of this method is tested for various images and combinations of lost blocks

Fast Image Restoration Method Based on the Multi-Resolution Layer

[[abstract]]When transmitted through a poor quality network or stored on an unstable storage media, block-based code images will experience the block loss. To restore damaged images suffering from block loss, Best Neighborhood Matching and Jump and Look-Around BNM provide the most effective image restoration. However, while BNM offers good restoration quality, it requires a large calculation time. By “JUMP” method, JLBNM can effectively shorten the computation time but this comes at the cost of a loss in quality. We have therefore proposed a new image inpainting technique that uses theWavelet Domain to deliver fast computation time and high restoration quality Wavelet Stage BNM. Our proposed reconstruction algorithm includes three optimization techniques change of analytical domain, consideration of texture composition and a new decision-making mechanism: DirectionalWaveletWeighted Method. Theoretical analysis and experimental results demonstrate our method delivered fast computation time and high restoration quality.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙

A Novel Technique of Error Concealment Method Selection in Texture Images Using ALBP Classifier

There are many error concealment techniques for image processing. In the paper, the focus is on restoration of image with missing blocks or macroblocks. Different methods can be optimal for different kinds of images. In recent years, great attention was dedicated to textures, and specific methods were developed for their processing. Many of them use classification of textures as an integral part. It is also of an advantage to know the texture classification to select the best restoration technique. In the paper, selection based on texture classification with advanced local binary patterns and spatial distribution of dominant patterns is proposed. It is shown, that for classified textures, optimal error concealment method can be selected from predefined ones, resulting then in better restoration. For testing, three methods of extrapolation and texture synthesis were used

Image Reconstruction Using Modified Hybrid Transform

In this paper, an algorithm for reconstruction of a completely lost blocks using Modified Hybrid Transform. The algorithms examined in this paper do not require a DC estimation method or interpolation. The reconstruction achieved using matrix manipulation based on Modified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detect the missing blocks for the purpose of rebuilding it. We further asses the performance of the Modified Hybrid Transform in lost block reconstruction application. Also this paper discusses the effect of using multiwavelet and 3D Radon in lost block reconstruction

Padding Block Based DVC Coding Scheme with Mutual Bi-directional Frame Coding at Decoder

[[abstract]]In this paper, we apply the mutual bi-directional frame coding (MB-frame coding) to our previous proposed padding block based Distributed Video Coding (DVC) scheme for performance improvement. Basically, in the MB-frame coding approach, we adopt the mutual forward and backward video sequence frames to process within reference frames in each individual Group of Pictures (GOP) until no skip blocks could be padded at decoder. It is worth to noting that with this approach the computation complexity does not increase at encoder side, which is consistent with the basic concept to meet the low complexity DVC requirement. Indeed, it achieves the overall system performance improvement with the cost of increasing for average 30 % of computation complexity at decoder side. Via computer simulation we show that the experimental results with the MB frame coding approach has about 0.2 dB gain over the one which does not employ the MB-frames coding s[[sponsorship]]ISPACS[[incitationindex]]EI[[conferencetype]]國際[[conferencedate]]20121104~20121107[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Taiwa

Fast Algorithms For Fragment Based Completion In Images Of Natural Scenes

Textures are used widely in computer graphics to represent fine visual details and produce realistic looking images. Often it is necessary to remove some foreground object from the scene. Removal of the portion creates one or more holes in the texture image. These holes need to be filled to complete the image. Various methods like clone brush strokes and compositing processes are used to carry out this completion. User skill is required in such methods. Texture synthesis can also be used to complete regions where the texture is stationary or structured. Reconstructing methods can be used to fill in large-scale missing regions by interpolation. Inpainting is suitable for relatively small, smooth and non-textured regions. A number of other approaches focus on the edge and contour completion aspect of the problem. In this thesis we present a novel approach for addressing this image completion problem. Our approach focuses on image based completion, with no knowledge of the underlying scene. In natural images there is a strong horizontal orientation of texture/color distribution. We exploit this fact in our proposed algorithm to fill in missing regions from natural images. We follow the principle of figural familiarity and use the image as our training set to complete the image

Fast inpainting algorithm for real-time video inpainting problem

The paper examines a simple and efficient method to solve the digital inpainting problem with a reasonable result by processing the information locally around the painting area. The method is based on a unique matrix transformation algorithm. It can guarantee transforming a non-negative matrix without rows and columns of all zero elements into another matrix with the same size but having both its column and row products equal to 1. The method is time and memory efficient so it can be used in many real time systems like video stream which may have protential inpainting problems

Combined Structure and Texture Image Inpainting Algorithm for Natural Scene Image Completion

Image inpainting or image completion refers to the task of filling in the missing or damaged regions of an image in a visually plausible way. Many works on this subject have been proposed these recent years. We present a hybrid method for completion of images of natural scenery, where the removal of a foreground object creates a hole in the image. The basic idea is to decompose the original image into a structure and a texture image. Reconstruction of each image is performed separately. The missing information in the structure component is reconstructed using a structure inpainting algorithm, while the texture component is repaired by an improved exemplar based texture synthesis technique. Taking advantage of both the structure inpainting methods and texture synthesis techniques, we designed an effective image reconstruction method. A comparison with some existing methods on different natural images shows the merits of our proposed approach in providing high quality inpainted images. Keywords: Image inpainting, Decomposition method, Structure inpainting, Exemplar based, Texture synthesi