In this paper, a simple medical image compression technique is proposed, that based on utilizing the residual of autoregressive model (AR) along with bit-plane slicing (BPS) to exploit the spatial redundancy efficiently. The results showed that the compression performance of the proposed techniques is improved about twice on average compared to the traditional autoregressive, along with preserving the image quality due to considering the significant layers only of high image contribution effects.

The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as  a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity U_g , liquid velocity U_L, liquid viscosity μ_L, and particle density ρ_s on bed porosity B_P and solid holdups ε_g were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid

Fractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal image co

The need for image compression is always renewed because of its importance in reducing the volume of data; which in turn will be stored in less space and transferred more quickly though the communication channels.
In this paper a low cost color image lossy color image compression is introduced. The RGB image data is transformed to YUV color space, then the chromatic bands U & V are down-sampled using dissemination step. The bi-orthogonal wavelet transform is used to decompose each color sub band, separately. Then, the Discrete Cosine Transform (DCT) is used to encode the Low-Low (LL) sub band. The other wavelet sub bands are coded using scalar Quantization. Also, the quad tree coding process was applied on the outcomes of DCT and

In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.

A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

In this paper, the combined source coding with Multi Carrier Code Division Multiple Access (MC-CDMA) system is proposed, where the transmission of the compressed image produced from source coding through Additive White Gaussian Noise (AWGN) channel for a single user and multi users. In which the (MC-CDMA) system removes Inter Symbol Interference (ISI) and Inter Carrier Interference (ICI). The hybrid compression system of Discrete Cosine Transform (DCT) and predictive coding (PC) technique are integrated as a source coding. The simulation results indicates that the transmission system of a single user was much better than the transmission system of multi users. When the number of users increased, the Bit Error Rate (BER) increased. For a

In this paper, a method is proposed to increase the compression ratio for the color images by
dividing the image into non-overlapping blocks and applying different compression ratio for these
blocks depending on the importance information of the block. In the region that contain important
information the compression ratio is reduced to prevent loss of the information, while in the
smoothness region which has not important information, high compression ratio is used .The
proposed method shows better results when compared with classical methods(wavelet and DCT).

<span>Digital audio is required to transmit large sizes of audio information through the most common communication systems; in turn this leads to more challenges in both storage and archieving. In this paper, an efficient audio compressive scheme is proposed, it depends on combined transform coding scheme; it is consist of i) bi-orthogonal (tab 9/7) wavelet transform to decompose the audio signal into low &amp; multi high sub-bands, ii) then the produced sub-bands passed through DCT to de-correlate the signal, iii) the product of the combined transform stage is passed through progressive hierarchical quantization, then traditional run-length encoding (RLE), iv) and finally LZW coding to generate the output mate bitstream.