scholarly journals Improved JPEG Coding by Filtering 8 × 8 DCT Blocks

2021 ◽  
Vol 7 (7) ◽  
pp. 117
Author(s):  
Yasir Iqbal ◽  
Oh-Jin Kwon

The JPEG format, consisting of a set of image compression techniques, is one of the most commonly used image coding standards for both lossy and lossless image encoding. In this format, various techniques are used to improve image transmission and storage. In the final step of lossy image coding, JPEG uses either arithmetic or Huffman entropy coding modes to further compress data processed by lossy compression. Both modes encode all the 8 × 8 DCT blocks without filtering empty ones. An end-of-block marker is coded for empty blocks, and these empty blocks cause an unnecessary increase in file size when they are stored with the rest of the data. In this paper, we propose a modified version of the JPEG entropy coding. In the proposed version, instead of storing an end-of-block code for empty blocks with the rest of the data, we store their location in a separate buffer and then compress the buffer with an efficient lossless method to achieve a higher compression ratio. The size of the additional buffer, which keeps the information of location for the empty and non-empty blocks, was considered during the calculation of bits per pixel for the test images. In image compression, peak signal-to-noise ratio versus bits per pixel has been a major measure for evaluating the coding performance. Experimental results indicate that the proposed modified algorithm achieves lower bits per pixel while retaining quality.

2013 ◽  
Vol 860-863 ◽  
pp. 2946-2949
Author(s):  
Yu Li ◽  
Lin He

With the rapid development of the Internet era, in order to improve the speed of image transmission and storage, this paper presents a new method to use Walsh transform on data block which size is not 2n. And this paper focuses on the research of Walsh transform application in color image compression coding. The method is simple and can get good result through the experimental simulation.


2011 ◽  
Vol 19 (1) ◽  
Author(s):  
Y. Hu ◽  
J. Chuang ◽  
C. Lo ◽  
C. Li

AbstractIn this paper, a novel greyscale image coding technique based on vector quantization (VQ) is proposed. In VQ, the reconstructed image quality is restricted by the codebook used in the image encoding/decoding procedures. To provide a better image quality using a fixed-sized codebook, the codebook expansion technique is introduced in the proposed technique. In addition, the block prediction technique and the relatively address technique are employed to cut down the required storage cost of the compressed codes. From the results, it is shown that the proposed technique adaptively provides better image quality at low bit rates than VQ.


Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1680
Author(s):  
Gangtao Xin ◽  
Pingyi Fan

Soft compression is a lossless image compression method that is committed to eliminating coding redundancy and spatial redundancy simultaneously. To do so, it adopts shapes to encode an image. In this paper, we propose a compressible indicator function with regard to images, which gives a threshold of the average number of bits required to represent a location and can be used for illustrating the working principle. We investigate and analyze soft compression for binary image, gray image and multi-component image with specific algorithms and compressible indicator value. In terms of compression ratio, the soft compression algorithm outperforms the popular classical standards PNG and JPEG2000 in lossless image compression. It is expected that the bandwidth and storage space needed when transmitting and storing the same kind of images (such as medical images) can be greatly reduced with applying soft compression.


1997 ◽  
Vol 08 (01) ◽  
pp. 119-177 ◽  
Author(s):  
Christine I. Podilchuk ◽  
Robert J. Safranek

The area of image and video compression has made tremendous progress over the last several decades. The successes in image compression are due to advances and better understanding of waveform coding methods which take advantage of the signal statistics, perceptual methods which take advantage of psychovisual properties of the human visual system (HVS) and object-based models especially for very low bit rate work. Recent years have produced several image coding standards—JPEG for still image compression and H.261, MPEG-I and MPEG-II for video compression. While we have devoted a special section in this paper to cover international coding standards because of their practical value, we have also covered a large class of nonstandard coding technology in the interest of completeness and potential future value. Very low bit rate video coding remains a challenging problem as does our understanding of the human visual system for perceptually optimum compression. The wide range of applications and bit rates, from video telephony at rates as low as 9.6 kbps to HDTV at 20 Mbps and higher, has acted as a catalyst for generating new ideas in tackling the different challenges characterized by the particular application. The area of image compression will remain an interesting and fruitful area of research as we focus on combining source coding with channel coding and multimedia networking.


Author(s):  
Wurod Qasim Mohamed ◽  
Marwa Al–Sultani ◽  
Haraa Raheem Hatem

The modern technologies of the image transmission look for ultra-reducing of the error transmission in addition to enhancing the security over a wireless communication channel. This paper is applied and discussed two different techniques to achieve these requirements, which are linear block code (LBC) and two-dimensions (2-D) interleaving approach. We investigate a new approach of 2-D interleaving that increases the security of the image transmission and helps to diminution the bit error probability (BER). Using an investigated 2-D interleaving grouping LBC approach on image transmission, the system achieves a higher-security information and a better BER comparing with the other systems. It was done by means of peak signal to noise ratio (PSNR) and histogram analysis tests. Simulation results state these enhancements.


Scanned Document Image compression is an important technology for digital image transmission and storage. This study proposes a unique image compression system based on discrete curvelet transform & discrete wavelet Transform (DC-DWT) with a varying pixels position. The discrete wavelet and the Curvelet transform technique, which because of their outcomes and characteristics, DWT and CT are the most suitable technology for the varied field of image processing. The position of a pixel in the document images and the high-impact components are handled using the curve let transform technique during the compression of the JPEG image. The Cuckoo search algorithm is used for image enhancement. Depending on two primary criteria checks, excellent outcomes were achieved; the compression ratio and the quality of recreated scan document.


2019 ◽  
Vol 8 (4) ◽  
pp. 1927-1932

Text and image data are important elements for information processing almost in all the computer applications. Uncompressed image or text data require high transmission bandwidth and significant storage capacity. Designing and compression scheme is more critical with the recent growth of computer applications. Among the various spatial domain image compression techniques, multi-level Block partition Coding (MLBTC) is one of the best methods which has the least computational complexity. The parameters such as Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are measured and it is found that the implemented methods of BTC are superior to the traditional BTC. This paves the way for a nearly error free and compressed transmission of the images through the communication channel.


2021 ◽  
Vol 38 (4) ◽  
pp. 993-1006
Author(s):  
Vimala Kumari Gollu ◽  
Ganta Usha Sravani ◽  
Mandru Sunil Prakash ◽  
Ganta Srikanth

In recent times, medical scan images are crucial for accurate diagnosis by medical professionals. Due to the increasing size of the medical images, transfer and storage of images require huge bandwidth and storage space, and hence needs compression. In this paper, multilevel thresholding using 2-D histogram is proposed for compressing the images. In the proposed work, hybridization of optimization techniques viz., Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Symbiotic Organisms Search (SOS) is used to optimize the multilevel thresholding process by assuming the Renyi entropy as an objective function. Meaningful clusters are possible with optimal threshold values, which lead to better image compression. For performance evaluation, the proposed work has been examined on six Magnetic Resonance (MR) images of brain and compared with individual optimization techniques as well as with 1-D histogram. Recent study reveals that peak signal to noise ratio (PSNR) fail in measuring the visual quality of reconstructed image because of mismatch with the objective mean opinion scores (MOS). So, we incorporate weighted PSNR (WPSNR) and visual PSNR (VPSNR) as performance measuring parameters of the proposed method. Experimental results reveal that hGAPSO-SOS method can be accurately and efficiently used in problem of multilevel thresholding for image compression.


Author(s):  
Adnan Alam Khan ◽  
Dr. Asadullah Shah ◽  
Saghir Muhammad

Telemedicine is one of the most emerging technologies of applied medical sciences. Medical information related to patients is transmitted and stored for references and consultations. Medical images occupy huge space; in order to transmit these images may delay the process of image transmission in critical times. Image compression techniques provide a better solution to combat bandwidth scarcity problems, and transmit same image in a much lower bandwidth requirements, more faster and at the same time maintain quality. In this paper a differential image compression method is developed in which medical images are taken from a wounded patient and are compressed to reduce the bit rate of these images. Results indicate that on average 25% compression on images is achieved with 3.5 MOS taken from medical doctors and other paramedical staff the ultimately user of the images.


Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1817
Author(s):  
Jiawen Xue ◽  
Li Yin ◽  
Zehua Lan ◽  
Mingzhu Long ◽  
Guolin Li ◽  
...  

This paper proposes a novel 3D discrete cosine transform (DCT) based image compression method for medical endoscopic applications. Due to the high correlation among color components of wireless capsule endoscopy (WCE) images, the original 2D Bayer data pattern is reconstructed into a new 3D data pattern, and 3D DCT is adopted to compress the 3D data for high compression ratio and high quality. For the low computational complexity of 3D-DCT, an optimized 4-point DCT butterfly structure without multiplication operation is proposed. Due to the unique characteristics of the 3D data pattern, the quantization and zigzag scan are ameliorated. To further improve the visual quality of decompressed images, a frequency-domain filter is proposed to eliminate the blocking artifacts adaptively. Experiments show that our method attains an average compression ratio (CR) of 22.94:1 with the peak signal to noise ratio (PSNR) of 40.73 dB, which outperforms state-of-the-art methods.


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