Structure and Texture Filling-In of Missing Image Blocks in Wireless Transmission and Compression Applications
Abstract: 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 8 x 8 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 neighbors. If the lost block contained structure, it is reconstructed using an image in painting 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. The viability of this method for image compression, in association with loss JPEG, is also discussed.

Structure and Texture Filling-In of Missing Image Blocks in Wireless Transmission and Compression Applications


INTRODUCTION
lossy JPEG compression is used for general purpose images. The JPEG algorithm divides the image into blocks of 8 by 8 pixels and calculates a two-dimensional discrete cosine transform (DCT), followed by quantization and
Huffman encoding. a single block or several consecutive blocks of an image maybe lost when transmitted over the wireless channel. even if a single block is lost,
the remaining blocks in that line might be received without their correct dc value because JPEG uses differential encoding for storing the dc value of successive pixels. forward error
correction (FEC) and automatic retransmission query protocols
(ARQ) are the main techniques used to make the transmisson more robust.

PROPOSED ALGORITHM
The following three computationally
efficient steps are followed for reconstruction of the lost block:
1)classify lost blocks into texture and structure
2)synthesize blocks which were classified as texture (use
texture synthesis);
3)fill in blocks which were classified as structure (use image
inpainting).


Block Classification:
This decision is taken at the receiver
by querying the region surrounding the lost block.we use
a simple coarseness measure given by the number of local extrema
in the neighborhood of the lost block To determine
whether or not a block has texture or noise.

Texture Synthesis:
when a block is classified as having texture, the entire 8-neighborhood of that block has texture. The missing block is then filled-in with the
texture from its surrounding.

Image Inpainting:
Structure in an image can be an edge between two regions or
a deterministic change in color or gray value.the digital inpainting procedure is applied when the block
classification algorithm detects a structured block.


For more details refer this pdf:
http://ivms.stanford.edu/~srane/papers/r...eetrip.pdf
ima.umn.edu/preprints/scanned-preprint/preprints5/1766.pdf