Coding Algorithm for Grayscale Images – Design of Piecewise Uniform Quantizer with Golomb–Rice Code and Novel Analytical Model for Performance Analysis
Pub. online:1 Jan 2017Type:Research ArticleOpen Access
Journal:Informatica
Volume 28, Issue 4 (2017), pp. 629–649
Abstract
World has become a global village after introduction of social media and social networks. However, it extensively increased the demand for network resources, particularly multimedia traffic like images, videos and audio. The medium for this extensive traffic is always public networks such as internet or cellular networks. But the open nature of such network like internet always creates security threats for data during transmission. Due to many intrinsic features and higher correlation in multimedia traffic, existing encryption algorithms are not very convincing to perform well under critical scenarios. Therefore, many people in the research community are still working to propose new encryption schemes which can address these issues and handle multimedia traffic effectively on public networks. In this paper, we explore the weaknesses of existing encryption schemes, which compromise in many scenarios due to high correlation of multimedia traffic. To tackle this issue we proposed certain enhancements in an existing scheme. Our enhanced modification includes addition of bitwise XORed operation using non-linear chaotic algorithm. Performance of enhanced scheme is tested against state of the art security parameters. Efficiency of the proposed scheme is also validated via entropy, correlation, peak signal to noise ratio, unified average change intensity and number of pixels change rate tests.
Journal:Informatica
Volume 27, Issue 3 (2016), pp. 527–548
Abstract
This paper presents a model for signal compression, which consists of a piecewise uniform quantizer and a new lossless coder. The model is designed in a general manner, i.e. for any symmetrical signal distribution; this general theory is applied to design models for Gaussian and Laplacian distributions. Rigorous mathematical derivation of the expression for the bit-rate is presented. Forward adaptation of the model is done for non-stationary signals. Theory is proved by simulations in MATLAB and by an experiment with a real speech signal. The most important advantages of the model are low complexity and good performances – it satisfies G.712 standard for the speech transmission quality with 6.18 bps (bits per sample), which is significantly smaller than 8 bps required for quantizers used in PSTN (public switched telephone network) defined with G.711 standard.
Journal:Informatica
Volume 25, Issue 4 (2014), pp. 523–540
Abstract
Abstract
Reversible data hiding is a method that can guarantee that the cover image can be reconstructed correctly after the secret message has been extracted. Recently, some reversible data hiding schemes have concentrated on the VQ compression domain. In this paper, we present a new reversible data hiding scheme based on VQ and SMVQ techniques to enhance embedding capacity and compression rate. Experimental results show that our proposed scheme achieves higher embedding capacity and smaller average compression rate than some previous methods. Moreover, our proposed scheme maintains the high level of visual quality of the reconstructed image.
Journal:Informatica
Volume 23, Issue 1 (2012), pp. 125–140
Abstract
In this paper, a piecewise uniform quantizer for input samples with discrete amplitudes for Laplacian source is designed and analyzed, and its forward adaptation is done. This type of quantizers is very often used in practice for the purpose of compression and coding of already quantized signals. It is shown that the design and the adaptation of quantizers for discrete input samples are different from the design and the adaptation of quantizers for continual input samples. A weighting function for PSQNR (peak signal-to-quantization noise ratio), which is obtained based on probability density function of variance of standard test images is introduced. Experiments are done, applying these quantizers for compression of grayscale images. Experimental results are very well matched to the theoretical results, proving the theory. Adaptive piecewise uniform quantizer designed for discrete input samples gives for 9 to 20 dB higher PSQNR compared to the fixed piecewise uniform quantizer designed for discrete input samples. Also it is shown that the adaptive piecewise uniform quantizer designed for discrete input samples gives higher PSQNR for 1.46 to 3.45 dB compared the adaptive piecewise uniform quantizer designed for continual input samples, which proves that the discrete model is more appropriate for image quantization than continual model.
Journal:Informatica
Volume 2, Issue 1 (1991), pp. 100–116
Abstract
The hierarchical principle of video-information analysis (progressive detalisation) is one from the set of principles which are implemented in the living vision system. The reflection of this principle in the techniques of the representation of a shape of the region, occupied by binary image, allows us to find a solution of two tasks simultaneously: data compression and data structure, which suits for geometric transformations of the image. This report includes operations which are performed on the hierarchical list of rectangles. The latter is built up by using intermediate pyramidal representation.