AI Summary & Key Takeaways
AI InsightHere, we benefit of neighborhood relation of pixels for each color plane by using a new iterative block, named as ''Adaptive Wiener-Turbo'' scheme, which employs Turbo decoder, JPEG encoder/decoders and Adaptive Wiener Filtering.
📌 3 Key Takeaways
Abstract
In order to improve unequal error protection and compression ratio of 2-D colored images over wireless environment, we propose two new schemes denoted as ''Adaptive Wiener-Turbo System (AW-TS) and Adaptive Wiener-Turbo Systems with JPEG & Bit Plane Compressions (AW-TSwJBC)''. In AW-TS, there is a feedback link between Wiener filtering and Turbo decoder and process iteratively. The scheme employs a pixel-wise adaptive Wiener-based Turbo decoder and uses statistics (mean and standard deviation of local image) of estimated values of local neighborhood of each pixel. It has extra-ordinary satisfactory results of both bit error rate (BER) and image enhancement performance for less than 2 dB Signal-to-Noise Ratio (SNR) values, compared to separately application of traditional turbo coding scheme and 2-D filtering.In AW-TSwJBC scheme, 2-D colored image is passed through a color & bit planes� slicer block. In this block, each pixel of the input image is partitioned up to three main color planes as R,G,B and each pixel of the color planes is sliced up to N binary bit planes, which corresponds to binary representation of pixels. Thus depending on importance of information knowledge of the input image, pixels of each color plane can be represented by fewer number of bit planes. Then they are compressed by JPEG prior to turbo encoder. Hence, two consecutive compressions are achieved regarding the input image. In 2-D images, information is mainly carried by neighbors of pixels. Here, we benefit of neighborhood relation of pixels for each color plane by using a new iterative block, named as ''Adaptive Wiener-Turbo'' scheme, which employs Turbo decoder, JPEG encoder/decoders and Adaptive Wiener Filtering.