• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.169-172
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• 2005

Genetic algorithm based predictor for lossless image compression is propsed. We describe a genetic algorithm to learn predictive model for lossless image compression. The error image can be further compressed using entropy coding such as Huffman coding or arithmetic coding. We show that the proposed algorithm can be feasible to lossless image compression algorithm.

• 전기학회논문지P
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• 제58권3호
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• pp.285-290
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• 2009

In this paper, we propose a new algorithm that improves the lossless data compression rate. The proposed algorithm lessens the redundancy and improves the compression rate evolutionarily around 40 up to 80 percentile depending on the characteristics of binary images used for compression. In order to demonstrate the superiority of the proposed method, the comparison between the proposed method and the LZ78 (LZ77) is demonstrated through experimental results theoretical analysis.

• 대한임베디드공학회논문지
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• 제19권4호
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• pp.195-201
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• 2024

In this paper, we propose an improved technique called HAB (Huffman encoding Aware Bitpacking) that enhances the Sprintz method, which is a representative time series data compression technique. The proposed technique boosts compression rates by incorporating Huffman encoding-aware bitpacking in the secondary compression stage. Additionally, it can be applied to terminal nodes or edge nodes with limited available resources, as it does not require separate parameters or storage space for compression. The proposed technique is a lossless method and is suitable for fields that require the generation of artificial intelligence models and accurate data analysis. In the experimental evaluation, the proposed HAB showed an average improvement of 14.7% compared to the existing technique in terms of compression rate.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2485-2489
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• 2005

This paper introduces a new preprocessing scheme to replace original data of gray scale images with particular ordered data so that performance of lossless compression can be improved more efficiently. As a kind of preprocessing technique to maximize performance of entropy encoder, the proposed method converts the input image data into more compressible form. Before encoding a stream of the input image, the proposed preprocessor counts co-occurrence frequencies for neighboring pixel pairs. Then, it replaces each pair of adjacent gray values with particular ordered numbers based on the investigated co-occurrence frequencies. When compressing ordered image using entropy encoder, we can expect to raise compression rate more highly because of enhanced statistical feature of the input image. In this paper, we show that lossless compression rate increased by up to 37.85% when comparing results from compressing preprocessed and non-preprocessed image data using entropy encoder such as Huffman, Arithmetic encoder.

• Journal of Information Processing Systems
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• 제12권2호
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• pp.322-331
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• 2016

Image compression is an essential technique for saving time and storage space for the gigantic amount of data generated by images. This paper introduces an adaptive source-mapping scheme that greatly improves bit-level lossless grayscale image compression. In the proposed mapping scheme, the frequency of occurrence of each symbol in the original image is computed. According to their corresponding frequencies, these symbols are sorted in descending order. Based on this order, each symbol is replaced by an 8-bit weighted fixed-length code. This replacement will generate an equivalent binary source with an increased length of successive identical symbols (0s or 1s). Different experiments using Lempel-Ziv lossless image compression algorithms have been conducted on the generated binary source. Results show that the newly proposed mapping scheme achieves some dramatic improvements in regards to compression ratios.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.756-761
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• 1998

This paper describes an in-line lossless data compression method using adaptive binary arithmetic coding. To achieve better compression efficiency , we employ an adaptive fuzzy -tuning modeler, which uses fuzzy inference to deal with the problem of conditional probability estimation. The design is simple, fast and suitable for VLSI implementation because we adopt the table -look-up approach. As compared with the out-comes of other lossless coding schemes, our results are good and satisfactory for various types of source data.

• ETRI Journal
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• 제28권2호
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• pp.260-263
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• 2006

This letter proposes a new near-lossless image compression method with only one line buffer cost for a digital camera with Bayer format image. For such format data, it can provide a low average compression rate (4.24bits/pixel) with high-image quality (larger than 46.37dB where the error of every pixel is less than two). The experimental results show that the near-lossless compression method has better performance than JPEG-LS (lossless) with ${\delta}$ = 2 for a Bayer format image.

• 한국음향학회지
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• 제28권7호
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• pp.618-629
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• 2009

The MPEG-4 Audio Lossless Coding (ALS) standard belongs to the family MPEG-4 audio coding standards. In contrast to lossy codecs such as AAC, which merely strive to preserve the subjective audio quality, lossless coding preserves every single bit of the original audio data. The ALS core codec is based on forward-adaptive linear prediction, which combines remarkable compression with low complexity. Additional features include long-term prediction, multichannel coding, and compression of floating-point audio material. This paper describes the basic elements of the ALS codec with a focus on prediction, entropy coding, and related tools and points out the most important applications of this standardized lossless audio format.

• 인터넷정보학회논문지
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• 제21권4호
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• pp.43-49
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• 2020

본 논문은 입력 영상 데이터를 블록 적응적으로 Context Tree Weighting을 사용하여 산술 부호 기반의 무손실 영상 압축 방법을 제안한다. CTW 기법은 입력 데이터를 비트 단위로 예측 및 압축을 하는 특성을 가진다. 또한, CTW 기법은 미지의 모델 및 파라미터에 대해서도 효율적인 압축을 한다는 점에서 장점을 보여준다. 본 연구에서는 무손실 압축이 필요한 항공 및 위성 사진을 옵션 정보에 따라 분할한 다음 각각 CTW 기반의 산술 부호기를 적용하여 압축의 효율을 증대하고자 한다. 항공 및 위성 사진은 영상 내 정보의 가치가 높으므로 무손실 압축이 불가피하다. 또한, 영상 크기가 일반적인 영상에 비해 크기 때문에 고압축 역시 필요하다. 기존의 무손실 압축 기법으로는 대용량의 중요 영상을 압축하는 데에 어려움이 존재한다. 이러한 이유로, 본 논문에서는 분할하지 않은 영상을 압축할 때 보다 제안하는 방법을 통해 영상을 압축했을 때 더 높은 압축률을 보여주기 위한 실험을 제공한다. 실험을 통해 기존의 무손실 압축 기법을 사용하여 압축을 진행했을 때 보다 CTW 기법을 이용하여 분할한 영상을 압축했을 때의 압축률이 더 높음을 확인할 수 있다.

• 정보처리학회논문지C
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• 제8C권5호
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• pp.525-534
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• 2001

일반적으로 무손실 영상압축 및 암호화 방법에는 압축과 암호화 과정이 독립적으로 이루어진다. 압축 후 암호화를 수행하면 압축열이 암호에 대한 평문으로 사용되므로 압축에 따른 엔트로피가 감소하여 랜덤한 성질을 갖게된다. 그러나 압축열 전체에 대한 암호화는 수행시간이 길어져 실시간 처리를 저해하는 원인이 되기도 한다. 본 논문에서는 무손실 영상압축과 암호의 결합에서 전체 처리시간을 줄이는 방법을 제안한다. 이는 쿼드트리 압축 알고리즘으로 그레이 영상을 분해하여 구조부분만을 암호화하는 방법이다. 아울러 영상의 무상관성과 동질영역을 확보하기 위한 변환과정을 수행하여 무손실 압축성능을 개선하였고, 쿼드트리 분해시 암호화되지 않은 데이터를 레벨별로 재구성하여 안전성을 갖도록 하였다. 모의 실험을 통하여 제안한 방법이 영상 압축율의 개선과 암호화 방법의 안전성 확보 및 실시간 처리가 가능함을 확인하였다.