ACO:lossless quality score compression based on adaptive coding order

Background: With the rapid development of high-throughput sequencing technology, the cost of whole genome sequencing drops rapidly, which leads to an exponential growth of genome data. Although the compression of DNA bases has achieved significant improvement in recent years, the compression of quality score is still challenging.Results: In this paper, by reinvestigating the inherent correlations between the quality score and the sequencing process, we propose a novel lossless quality score compressor based on adaptive coding order (ACO). The main objective of ACO is to traverse the quality score adaptively in the most correlative trajectory according to the sequencing process. By cooperating with the adaptive arithmetic coding and context modeling, ACO achieves the state-of-the-art quality score compression performances with moderate complexity.Conclusions: The competence enables ACO to serve as a candidate tool for quality score compression, ACO has been employed by AVS(Audio Video coding Standard Workgroup of China) and is freely available at https://github.com/Yoniming/code.

IMPLEMENTASI ALGORITMA KOMPRESI ADAPTIVE ARITHMETIC CODING PADA APLIKASI PENYIMPANAN FILE ONLINE

Along with the development of technology at this time some programmers have found a solution to overcome the problem of storing important files that we worried about before the file security by making several applications that we often refer to as online file storage. Files saved to online file storage are usually document files and image files. However, the problem that arises is the image file has a large size and takes up large storage space and requires a long time in the process of exchanging data. To reduce the size of an image file compression techniques can be used. Compression is a way to compress data so that it only requires a smaller storage space so that it is efficient in storing or shortening time in exchanging information. Compression technique has several algorithms, in this study the authors used the Adaptive Arithmetic Coding algorithm. From the results of the study the authors managed to compress a color image file with jpg extension using the Adaptive Arithmetic Coding algorithm. The application produced in this research is a web designed using Dreamweaver CS5 and php programming language.Keywords: Compression, Adaptive Arithmetic Coding, DreamweaverCS5, PHP.

Significance linked connected component analysis plus

An image coding algorithm, SLCCA Plus, is introduced in this dissertation. SLCCA Plus is a wavelet-based subband coding method. In wavelet-based subband coding, the input images will go through a wavelet transform and be decomposed into wavelet subband pyramids. Then the characteristics of the wavelet coefficients within and among subbands will be utilized to removing the redundancy. The rest information will be organized and go through entropy encoding. SLCCA Plus contains a series improvement method to the SLCCA. Before SLCCA, there are three top-ranked wavelet image coders. Namely, Embedded Zerotree Wavelet coder (EZW), Morphological Representation of Wavelet Date (MEWD), and Set Partitioning in Hierarchical Trees (SPIHT). They exploit either inter-subband relation among zero wavelet coefficients or within-subband clustering. SLCCA, on the other hand, outperforms these three coders by exploring both the inter- subband coefficients relations and within-subband clustering of significant wavelet coefficients. SLCCA Plus strengthens SLCCA in the following aspects: Intelligence quantization, enhanced cluster filter, potential-significant shared-zero, and improved context models. The purpose of the first three improvements is to remove redundancy information further while keeping the image error as low as possible. As a result, they achieve a better trade-off between bit cost and image quality. Moreover, the improved context lowers the entropy by refining the classification of symbols in cluster sequence and magnitude bit-planes. Lower entropy means the adaptive arithmetic coding can achieve a better coding gain. For performance evaluation, SLCCA Plus is compared to SLCCA and JPEG2000. On average, SLCCA Plus achieves 7% bit saving over JPEG 2000 and 4% over SLCCA. The results comparison shows that SLCCA Plus shows more texture and edge details at a lower bitrate.