Variable block-size double predictor DPCM image data compression

In this paper we uses The Differential pulse code modulation (DPCM) to remove the unused bit in the image for image compression. In this paper we compare the compressed image for 1 and 3 bit/pixel using DPCM and also compare the estimation error. We decrease the compressed image distortion and the estimation error. The PMSE in 3bit/pixel DPCM less 9-10 dB compare to 1bit/pixel DPCM.

2012

Image processing modifies pictures to improve, extract information and change their structure (composition, image editing, and image compression etc.). Images can be processed by optical, photographic and electronic means, but image processing using digital computers are the most common method because digital methods are fast, flexible and precise. Compression reducing the redundancy in the image data to optimize transmission / storage. The DPCM and LMS may be used to remove the unused bit in the image for image compression. In this paper we compare the compressed image results for 1 and 3 bits DPCM Quantzation and DPCM with LMS Algorithm and also compare the histogram, prediction mean square using DPCM Quantzation and DPCM with LMS Algorithm for approximately same distortion levels. The LMS may provide almost 2 bits per pixel reduction in transmitted bit rate compared to DPCM when distortion levels are approximately the same distortion for both methods. The LMS Algorithm may be use...

The Differential pulse code modulation (DPCM) may be used to remove the unused bit in the image for image compression.

International Journal of Signal Processing, Image Processing and Pattern Recognition, 2014

A novel color image compression scheme based on block truncation coding is proposed in this paper. In this scheme, the quadtree segmentation technique is employed to partition the color image into variable-sized image blocks according to its block activities. Then, the block truncation coding scheme with the bit map omission technique is employed to encode the image blocks. According to the experimental results, the proposed scheme significantly cuts down the bit rates while keeping good reconstructed image qualities of the compressed color images.

2020

In this paper the image compression technique uses both Wavelet transformation technique and Quad tree decomposition technique simultaneously, for better compression performance. Here the compression ratio (CR) as well as the peak signal to noise ratio (PSNR) value has been better than any one of the techniques, that will be shown in the simulation result. Generally, discrete wavelet transformation (DWT) decomposes an image into a hierarchical subbands system consists of some significant coefficients of the image depending upon space frequency localization technique. A quadtree decomposition technique is then applied on the resultant image of the wavelet decomposition, which is divided into some blocks that contains image information and other details depending on a given threshold, followed by an entropy encoding technique which finally compress the image. The simulation is done by mat lab.

1996

This paper describes tools for the theoretical and experimental study of several DPCM methods in image acquisition and compression, with applications in Intelligent Visual Sensor development. The paper also presents conclusions about DSP based implementations of the described algorithms.

Tikrit Journal of Engineering Sciences

By the nature of images, picture elements in local regions are highly correlated with one another. In such cases, image compression techniques are introduced to reduce the amount of data is needed to represent the same information, either exactly or approximately. In this work DCT/DPCM hybrid approach have been designed and implemented for interlaced images. The image signal was first transformed row-wise using discrete cosine transform (DCT) and a differential pulse code modulation (DPCM) scheme then was used column-wise to get difference signal. For still images the same 3-bit quantizer was employed which makes quantization process easier. For interlaced images 3-bit quantizer was used for the odd field and 2-bit quantizer for even field, since the difference signal of the even field was very small. A compression ratios of about 13:1 was obtained for interlaced image. Objective measurements showed a high peak to peak signal to noise ratio without noticeable impairment.

International Journal of Applied Information Systems, 2014

This paper proposed FPGA implementation of variant DPCM based image compression technique (Multiple LUT-DPCM). Image compression addresses the problem of reducing the amount of data required to represent a digital image. Such data compression can be achieved by reducing the redundancies of the image data in order to be able to store or transmit data in an efficient form. There are various onboard data compression techniques used in image processing. Out of which DPCM based compression technique is the most commonly used one. For the hardware implementation, an algorithm for Multiple LUT DPCM is designed. VHDL code is developed based on the algorithm designed. After simulation and verification of developed code with test data generated, it implemented in to hardware. The developed hardware's functionality, then verified with the already simulated data and also with real image data.

International Journal of Information Technology Convergence and Services, 2012

This paper work describes the implementation of Discrete Wavelet Transform based progressive block coder using only quad-tree partitioning approach. The motivation behind this work is from SPECK (Set Partitioning Embedded bloCK) algorithm. It uses set partitioning and significance testing on hierarchical structures of transformed images in a recursive manner. The proposed method simplifies the complexity of the embedded wavelet image coding algorithm by combining both sorting pass and refinement pass. In comparison with other methods, this is simpler to be realized on hardware and has higher compression efficiency. The implementation is done by using TMS320C6713 DSK board. The statistical analysis is done with profile statistic available in Code Composer Studio (CCS) environment. The simulation results obtained in MATLAB environment show that PSNR values are quite improved by lowering threshold values.

Ieee Transactions on Signal Processing, 2007

Differential pulse code modulation (DPCM) is able to code highly correlated sources efficiently at high bit rates but not at low bit-rate regions. Motivated by the rate-distortion theory, a simple modified DPCM codec using multirate processing is proposed. A low-pass filter is used to limit the source signal spectrum according to the optimal mapping scheme. Bit rate reduction is achieved by reducing the number of transmitted samples through downsampling. A Wiener filter is appended at the decoder for further noise reduction. Simulation results agree with theoretical analysis and show that for a first-order autoregressive [AR(1)] process, the proposed codec makes substantial improvements over the classic DPCM and performs close to the rate-distortion bound. The proposed system is then implemented as a low-rate predictive image coder. In addition to apply two-dimensional DPCM, adaptive entropy coding is used to exploit variation in the local statistics of the prediction error image. Simulation results show that the system is able to outperform JPEG at low rates and has subjective quality comparable to that of JPEG2000.