Image Compression Using Hybrid(DCT+DWT) Technique- A Comparative Study

When the data is in uncompressed state it becomes difficult to store and transmit it. This problem can be addressed by image compression. Image compression reduces the number of bits per pixel of the image so that its storage and transmission becomes easy. Basic goal of image compression is to increase visual quality of image with less noise. The proposed methodology satisfies this aim. Hybrid of DCT (Discrete Cosine Transformation) and DWT (Discrete Wavelet Transformation) are combined to achieve this goal. Combined advantages of DCT and DWT are used as proposed methodology. DCT has high energy compaction and less number of computational resources are required while DWT has multi resolution transformation. Hybrid DCT-DWT is proposed to compress and reconstruct images. Also colorization of the reconstructed images is proposed. Reconstructed images are stored in gray format and to visualize it colorization is done on that gray scale image. Results show that this method of compression and colorization helps in compressing and retaining color of images

Hybrid Algorithmic Approach for Medical Image Compression Based on Discrete Wavelet Transform (DWT) and Huffman Techniques for Cloud Computing

As medical imaging facilities move towards complete filmless imaging and also generate a large volume of image data through various advance medical modalities, the ability to store, share and transfer images on a cloud-based system is essential for maximizing efficiencies. The major issue that arises in teleradiology is the difficulty of transmitting large volume of medical data with relatively low bandwidth. Image compression techniques have increased the viability by reducing the bandwidth requirement and cost-effective delivery of medical images for primary diagnosis.Wavelet transformation is widely used in the fields of image compression because they allow analysis of images at various levels of resolution and good characteristics. The algorithm what is discussed in this paper employs wavelet toolbox of MATLAB. Multilevel decomposition of the original image is performed by using Haar wavelet transform and then image is quantified and coded based on Huffman technique. The wavelet packet has been applied for reconstruction of the compressed image. The simulation results show that the algorithm has excellent effects in the image reconstruction and better compression ratio and also study shows that valuable in medical image compression on cloud platfor

Performance Analysis of Set Partitioning in Hierarchical Trees (spiht) Algorithm for a Family of Wavelets Used in Color Image Compression

With the spurt in the amount of data (Image, video, audio, speech, & text) available on the net, there is a huge demand for memory & bandwidth savings. One has to achieve this, by maintaining the quality & fidelity of the data acceptable to the end user. Wavelet transform is an important and practical tool for data compression. Set partitioning in hierarchal trees (SPIHT) is a widely used compression algorithm for wavelet transformed images. Among all wavelet transform and zero-tree quantization based image compression algorithms SPIHT has become the benchmark state-of-the-art algorithm because it is simple to implement & yields good results. In this paper we present a comparative study of various wavelet families for image compression with SPIHT algorithm. We have conducted experiments with Daubechies, Coiflet, Symlet, Bi-orthogonal, Reverse Bi-orthogonal and Demeyer wavelet types. The resulting image quality is measured objectively, using peak signal-to-noise ratio (PSNR), and subjectively, using perceived image quality (human visual perception, HVP for short). The resulting reduction in the image size is quantified by compression ratio (CR)

Image Compression and Watermarking scheme using Scalar Quantization

This paper presents a new compression technique and image watermarking algorithm based on Contourlet Transform (CT). For image compression, an energy based quantization is used. Scalar quantization is explored for image watermarking. Double filter bank structure is used in CT. The Laplacian Pyramid (LP) is used to capture the point discontinuities, and then followed by a Directional Filter Bank (DFB) to link point discontinuities. The coefficients of down sampled low pass version of LP decomposed image are re-ordered in a pre-determined manner and prediction algorithm is used to reduce entropy (bits/pixel). In addition, the coefficients of CT are quantized based on the energy in the particular band. The superiority of proposed algorithm to JPEG is observed in terms of reduced blocking artifacts. The results are also compared with wavelet transform (WT). Superiority of CT to WT is observed when the image contains more contours. The watermark image is embedded in the low pass image of contourlet decomposition. The watermark can be extracted with minimum error. In terms of PSNR, the visual quality of the watermarked image is exceptional. The proposed algorithm is robust to many image attacks and suitable for copyright protection applications.Comment: 11 Pages, IJNGN Journal 201

Hardware Architecture for the Implementation of the Discrete Wavelet Transform in two Dimensions

Resumen El artículo presenta una arquitectura hardware que desarrolla la transformada Wavelet en dos dimensiones sobre una FPGA, en el diseño se buscó un balance entre número de celdas lógicas requeridas y la velocidad de procesamiento. El artículo inicia con una revisión de trabajos previos, después se presentan los fundamentos teóricos de la transformación, posteriormente se presenta la arquitectura propuesta seguida por un análisis comparativo. El sistema se implementó en la FPGA Ciclone II EP2C35F672C6 de Altera utilizando un diseño soportado en el sistema Nios II. Abstract This paper presents a hardware architecture developed by the two-dimensional wavelet transform on an FPGA, in the design it was searched a balance between the number of required logic cells and the processing speed. The design is based on a methodology to reuse the input data with a parallel-pipelined structure and a calculation of the coefficients is performed using a method of odd and even numbers, which is achieved by calculating a cycle ratio after 2 cycles latency, to store the data processing result of the SDRAM memory is used IS42S16400, the control unit uses a design architecture supported by Nios II processor. The system was implemented in the FPGA Altera Cyclone II EP2C35F672C6 using a design that combines descriptions in VHDL, schematics and control connection via a general purpose processor

IMPROVED IMAGE COMPRESSION BASED WAVELET TRANSFORM AND THRESHOLD ENTROPY

In this paper, a method is proposed to increase the compression ratio for the color images by dividing the image into non-overlapping blocks and applying different compression ratio for these blocks depending on the importance information of the block. In the region that contain important information the compression ratio is reduced to prevent loss of the information, while in the smoothness region which has not important information, high compression ratio is used .The proposed method shows better results when compared with classical methods(wavelet and DCT)

Image Compression Effects in Face Recognition Systems

With the growing number of face recognition applications in everyday life, image- an