The quality of the RGB color image degrades from the minute it is captured to the time it is displayed to the human observer. The image is subject to many kinds of distortions during the stages that it might pass through such as storing, processing, compressing, and transmitting, thus enhancing the image quality is a major important issue. This paper will introduce the effects of salt&pepper and Gaussian noises. A comparative experimental analysis will be done and some recommendation will be approved in which filter to use to reduce the effect of the noise. General TermsColor image filtering methods KeywordsAdaptive median filter, median filter, average filter, noise, PSNR..
Abstract-Finite impulse response (FIR) digital filters are known to have many distinguishable features such as stability, linear phase characteristic at all frequencies and digital implementation as non-recursive structures. FIR filter design can be considered as an optimization problem. In this paper an estimation method of FIR filter parameters is proposed. The method relies on establishing a relationship between the signal input parameters and the filter parameters. An FIR lowpass filter was implemented and tested using various parameter values. The results showed efficient performance characteristics of FIR lowpass filters.Keywords-FIR lowpass filter, transition bandwidth, sampling frequency, window length, filter order, and stopband attenuation. I. INTRODUCTIONDesigning digital filters involves the determination of a set of filter coefficients to meet a set of design specifications. Digital filters can be classified in two categories: finite impulse response (FIR) filters and infinite impulse response (IIR) filters. By varying the weight of the coefficients and number of filter taps, virtually any frequency response characteristics can be realized with an FIR filter. FIR filter is an attractive choice because of the ease in design, linear phase shift property and stabilityDesigning an FIR digital filter require specifying passband, stopband, and transition band. In passband, frequencies are needed to be passed unattenuated. In stopband, frequencies needs to be passed attenuated. Transitionband contains frequencies which are lying between the passband and stopband. Therefore, the entire frequency range is split into one or even more passbands, stopbands, and transition bands. In practical, the magnitude is not necessary to be constant in the passband of a filter. A small amount of ripple is usually allowed in the passband. Similarly, the filter response does not to be zero in the stopband. A small, nonzero value is also tolerable in the stopband as shown in Fig 1. The transition band of the filter as shown in Fig.1 is between the passband and the stopband. The frequency ω p denotes the edge of the passband, and the band-edge frequency ωs defines the edge of the stopband. So, the difference of ω s and ω p is the width of the transition band, i.e. ω t = ω s -ω p .The ripple in the passband of the filter is denoted as δp, and the magnitude of the filter varies from 1-δp to 1+ δp. δs are the ripple in the stopband.Usually we use a Logarithmic scale to show the frequency response, hence, the ripple in the passband is 20log10δp dB, and the ripple in the stopband is 20log10δs dB. [[3], [4]] Different methods are used to design a lowpass filter such as: window method, frequency sampling method, and optimization method.In window method, a truncated ideal lowpass filter with a certain bandwidth is generated, and then we use a chosen window to get certain stopband attenuation. The filter order L can be adjusted to meet a specified roll-off rate in the transition band. Any finite-length (order) of the ideal lowpass impu...
Steganography is the art of hiding secret data within other information (such as wave file) that it cannot be detected, but only by its intended recipient. Embedding secret text in wave file is a difficult process. There are varying techniques for embedding information in wave files. In this research a new simple technique of hiding secret information using wave files were produced, regardless the simplicity this technique it will be accurate and high confident.This paper features a new technique that suggests that the secrete text is encoded through the use position vector into wave file. The position vector (PV) is to be initialized randomly and to be kept confidential between the sender and the receiver. The security level of this technique will be high and it can be increased by encrypting the secrete text or/and encrypt the wave file including the text.
Preserving confidentiality, integrity and authenticity of images is becoming very important. There are so many different encryption techniques to protect images from unauthorized access. Matrix multiplication can be successfully used to encrypt-decrypt digital images. In this paper we made a comparison study between two image encryption techniques based on matrix multiplication namely, segmentation and parallel methods.
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