Image compression is a serious issue in computer storage and transmission, that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless compression scheme of first stage that corresponding to second stage. The tested results shown are promising in both two stages, that implicilty enhanced the performance of traditional polynomial model in terms of compression ratio , and preresving image quality.
The main goal of this paper is to introduce the higher derivatives multivalent harmonic function class, which is defined by the general linear operator. As a result, geometric properties such as coefficient estimation, convex combination, extreme point, distortion theorem and convolution property are obtained. Finally, we show that this class is invariant under the Bernandi-Libera-Livingston integral for harmonic functions.
The removal of SO2 from simulated gas stream (SO2 + air) in a fixed bed reactor using Modified Activated Carbon (MAC) catalysts was investigated. All the experiments were conducted at atmospheric pressure, initial SO2 concentration of 2500 ppm and bed temperature of 90oC. MAC was prepared by loading a series of nickel and copper oxides 1, 3, 5, 7, and 10 w
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