Abstract

In this paper, based on the parametric model of the matrix of discrete cosine transform (DCT), and using an exhaustive search of the parameters’ space, we seek for the best approximations of 8-point DCT at the given computational complexities by taking into account three different scenarios of practical usage. The possible parameter values are selected in such a way that the resulting transforms are only multiplierless approximations, i.e., only additions and bit-shift operations are required. The considered usage scenarios include such cases where approximation of DCT is used: (i) at the data compression stage, (ii) at the decompression stage, and (iii) both at the compression and decompression stages. The obtained results in effectiveness of generated approximations are compared with results of popular known approximations of 8-point DCT of the same class (i.e., multiplierless approximations). In addition, we perform a series of experiments in lossy compression of natural images using popular JPEG standard. The obtained results are presented and discussed. It should be noted, that in the overwhelming number of cases the generated approximations are better than the known ones, e.g., in asymmetric scenarios even by more than 3 dB starting from entropy of 2 bits per pixel. In the last part of the paper, we investigate the possibility of hardware implementation of generated approximations in Field-Programmable Gate Array (FPGA) circuits. The results in the form of resource and energy consumption are presented and commented. The experiment outcomes confirm the assumption that the considered class of transformations is characterized by low resource utilization.

Highlights

  • The need to transmit and archive multimedia data is pervasive

  • 5 Results and discussion In order to verify the effectiveness of automatically generated approximations of 8point discrete cosine transform (DCT), we carried out experiments in compression of natural images including all of the considered scenarios

  • The obtained results are shown in the form of plots of image quality estimations evaluated with popular Peak Signal-to-Noise Ratio (PSNR) measure against the entropy expressed here as a number of bits per single pixel which, allows for direct evaluation of the obtained ratio of compression

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Summary

Introduction

The constantly growing capabilities of modern image acquisition devices impose high demands on present-day communication and data storage systems. The solution to this problem are lossy compression standards which allow for substantial reduction of multimedia data sizes with reasonable loss of image quality. The widely used standards for lossy compression of static images and video sequences take advantage of block quantization where input data is first decorrelated in the domain of linear transform, and subjected to scalar quantization. Since modern image compression standards partition input images into 8×8-pixel blocks, and assume the separability of two-dimensional discrete cosine transform, only 8-point DCT has to be taken into consideration in the process of searching for effective approximations

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