Performance Analysis of Regular and Irregular LDPC Codes on SPIHT Coded Image Data

The LDPC (Low Density Parity Check Code) has Shown interesting results for transmitting embedded bit streams over noisy communication channels. Performance comparison of regular and irregular LDPC codes with SPIHT coded image is done here. Different Error Sensitive classes of image data are obtained by using SPIHT algorithm as an image coder. Irregular LDPC codes map the more important class of data into a higher degree protection class to provide more protection. Different degree protection classes of an LDPC code improves the overall performance of data transmission against channel errors. Simulation results show the superiority of irregular LDPC over regular LDPC codes.

Novel method of data compression for the online detection signal of coal mine wire rope

Coal mine wire rope detection is related to personnel and production safety. With the Chinese coal mining trend tending towards deep mining, a considerable amount of data is critical for the online detection of deep well lifting wire rope. To improve the sampling rate, decrease the analysis processing time and realise real-time online detection, this paper proposes an online detection data compression processing method. The study focuses on the distortion compression method for the online detection signal of deep well hoisting wire rope. The set partitioning in hierarchical trees (SPIHT) algorithm is one of the most advanced methods in the field of image transformation coding. Compared with other coding algorithms, the SPIHT algorithm demonstrates desired characteristics such as a high signal-to-noise ratio, lower complexity and decreased computational load, among others. This paper discusses how, in combination with the image processing method, a compression coding method for the one-dimensional signal of the magnetic leakage detection of the mining wire rope is developed. Furthermore, the set partitioning sorting algorithm is investigated and analysed, the temporal orientation tree structure of the one-dimensional signal of the wavelet coefficient is defined for wire rope magnetic leakage detection and the SPIHT algorithm is presented, in addition to an example of the one-dimensional signal from the magnetic leakage detection of the wire rope. The results reveal that under the condition of the normalised mean square error (NMSE; NMSE < 0.01) of distortion, the compression ratio improved by 30%. The online detection signal lossy compression method proposed in this study has a considerable influence on the recovery of the original signal, in addition to a higher compression ratio and a reduced computation time, compared to the existing method.

Hybrid medical image compression method using quincunx wavelet and geometric actif contour

The purpose of this article is to find an efficient and optimal method of compression by reducing the file size while retaining the information for a good quality processing and to produce credible pathological reports, based on the extraction of the information characteristics contained in medical images. In this article, we proposed a novel medical image compression that combines geometric active contour model and quincunx wavelet transform. In this method it is necessary to localize the region of interest, where we tried to localize all the part that contain the pathological, using the level set for an optimal reduction, then we use the quincunx wavelet coupled with the set partitioning in hierarchical trees (SPIHT) algorithm. After testing several algorithms we noticed that the proposed method gives satisfactory results. The comparison of the experimental results is based on parameters of evaluation.

An Effective Progressive Image Transmission using Superpixel based Saliency Detection and Modified SPIHT Compression Algorithm

A new progressive image transmission system was proposed in this research paper for effective usage of communication bandwidth. At first, the superpixel based saliency detection method was used for segmenting the foreground region from the background region, because it gives more saliency information of an image with the benefit of color contrast. Then, Integer Wavelet Transform (IWT) was applied in the foreground image, which delivers A good quality of the image and also the compression ratio of the image was decent. Additionally, optimized neural network and modified Set Partitioned in Hierarchical Tree (SPIHT) algorithm were applied in the background image that delivers good rate distortion properties in the noise free environment and also enhances the image visual experience. In modified SPIHT, the sub-tree roots were not excluded that helps to encode and quantize the wavelet coefficients effectively. Also, it delivers more information to the image edges that effectively improves the subjective visual experience. Experiment report showed that the proposed work enhanced the Peak Signal to Noise Ratio (PSNR) upto 5dB compared to the existing work.