International Journal of Scientific and Research Publications, Volume 4, Issue 8, August 2014 1 ISSN 2250-3153 www.ijsrp.org Gray Level Based Power Adaptation for Wireless Transmission of Images M.Padmaja 1 , K.Prasuna 2 1 Department of ECE, Assistant Professor, VR Siddhartha Engineering College, Vijayawada (A.P), INDIA 2 Department of ECE, Assistant Professor, Vijaya Institute of Technology for women, Vijayawada (A.P), INDIA Abstract- Gray level Slicing is to highlight a specific range of gray values. Power Adaptation methods are presented for gray level slicing approaches. Power Adaptation methods aims in optimization of the resulting bit error rate by gray level slicing without preserving background and gray level slicing with background. This paper gives us an achievable increase in the proposed method rather than the conventional method with a better quality and the bit error rate is also optimized in proposed method rather than the former method with acceptable quality. Index Terms- Bit error Rate (BER), Gray level slicing, Power Adaptation, Wireless Channels I. INTRODUCTION y the advent of multimedia communications and the information superhighway has given rise to an enormous demand on high-performance communication systems.Multimedia transmission of signals over wireless links is considered as one of the prime applications of future mobile radio communication systems. However, such applications require the use of relatively high data rates (in the Mbps range) compared to voice applications. With such requirement, it is very challenging to provide acceptable quality of services as measured by the bit error rate (BER) due to the limitations imposed by the wireless communication channels such as fading and multipath propagation. Furthermore, the user mobility makes such a task more difficult because of the time varying nature of the channel. The main resources available to communications systems designers are power and bandwidth as well as system complexity. Thus, it is imperative to use techniques that are both power and bandwidth efficient for proper utilization of the communication resources. Power Adaptation has been an effective approach in the transmission of 2D signals over wireless channels. In the process of transmission, Quality is the major feature of the signal. Several enhancement techniques are used to emphasize and sharpen 2D signal features for display and analysis. Consequently, the enhancement methods are application specific and are often developed empirically. Some enhancement algorithms use both the spatial and frequency domains. The type of techniques includes point operations, where each pixel is modified according to a particular equation that is not dependent on other pixel values; mask operations, where each pixel is modified according to the values of the pixel's neighbors (using convolution masks); or global operations, where all the pixel values in the 2D signal are taken into consideration. Spatial domain processing methods include all three types, but frequency domain operations, by nature of the frequency transforms, are global operations. Of course, frequency domain operations can become "mask operations," based only on a local neighborhood, by performing the transform on small image blocks instead of the entire image. Enhancement is used as a preprocessing step in some computer vision applications to ease the vision task, for example, to enhance the edges of an object to facilitate guidance of a robotic gripper. Gray-scale modification (also called gray-level scaling) methods belong in the category of point operations and function by changing the pixel's (gray-level) values by a mapping equation. The mapping equation is typically linear (nonlinear equations can be modeled by piecewise linear models) and maps the original gray-level values to other, specified values. Typical applications include contrast enhancement and feature enhancement.The primary operations applied to the gray scale of an image are to compress or stretch it. II. SYSTEM MODEL The system model utilizes two different approaches for gray level slicing- Gray Level slicing without preserving background and Gray Level slicing with background. In the first approach, high values are displayed for a range of interest and low values in other areas. But the background information is discarded. In the second approach, the objective is to display high values for the range of interest and original gray level values in other areas. This approach preserves the background of the image. A binary phase shift keying digital communication system is considered for image transmission. Initially, the image is gray level sliced, sampled, quantized, and then coded into binary bits for transmission by the system. Each sample is coded into M bits. The transmitted signal is represented as 1 () ( ( ) ) 0 0 M St wb gt kM iT i ki b i k          (1) Where w i is the transmitted power and b ki is the information data (±1) of the ith bit in the kthi block of the M bits representing one of the samples, g(t) is a rectangular pulse shape of transmitted signal, and Tb is the bit duration. Index i represents the location of a bit within the M bits belonging to the same sample with M-1 the representing the most significant bit (MSB) and index 0 representing the least significant bits (LSB).The wireless channel is the AWGN channel. B