• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.11
• /
• pp.5547-5562
• /
• 2016

JPEG-LS is an international standard for lossless or near-lossless image-compression algorithms. In this paper, a simple method is proposed to improve the performance of the lossless JPEG-LS algorithm. With respect to JPEG-LS and its supplementary explanation, Golomb-Rice (GR) coding is mainly used for entropy coding, but it is not used for long codewords. The proposed method replaces a set of long codewords with a set of shorter location map information. This paper shows how efficiently the location map guarantees reversibility and enhances the compression rate in terms of performance. Experiments have also been conducted to verify the efficiency of the proposed method.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.2
• /
• pp.417-424
• /
• 2019

This paper presents the design of a JPEG-LS codec for lossless image compression from AR/VR device. The proposed JPEG-LS(: LosSless) codec is mainly composed of a context modeling block, a context update block, a pixel prediction block, a prediction error coding block, a data packetizer block, and a memory block. All operations are organized in a fully pipelined architecture for real time image processing and the LOCO-I compression algorithm using improved 2D approach to compliant with the SBT coding. Compared with a similar study in JPEG-LS, the Block-RAM size of proposed STB-FLC architecture is reduced to 1/3 compact and the parallel design of the predication block could improved the processing speed.

• Journal of Broadcast Engineering
• /
• v.9 no.3
• /
• pp.246-256
• /
• 2004

In this paper, we proposed a new lossless image compression algorithm. Lossless image compression has been used in the field that requires the accuracy and precision. Thus, application areas using medical unaging, prepress unaging, image archival systems, precious artworks to be preserved, and remotely sensed images require lossless compression. The compression ratio from lossless image compression has not been satisfactory, thus far. So, new method of lossless image compression has been investigated to get better compression efficiency. We have compared the compression results with the most typical compression methods such as CALIC and JPEG-LS. CALIC has shown the best compression-ratio among the existing lossless coding methods at the cost of the extensive complexity by three pass algorithm. On the other hand, JPEG-LS's compression-ratio is not higher than CALIC, but was adopted as an international standard of ISO because of the low complexity and fast coding process. In the proposed method, we adopted an adaptive predictor that can exploit the characteristics of individual images, and an adaptive arithmetic coding with multiple probability models. As a result, the proposed algorithm showed 5％ improvement in compression efficiency in comparison with JPEG-LS and showed comparable compression ratio with CALIC.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2000.11a
• /
• pp.45-48
• /
• 2000

본 논문은 현재 고성능 가역압축 부호화의 표준이 되는 JPEG-LS의 예측오차에 대한 확률분포를 결정하는 컨텍스트 모델링(context modelling)에서 컨텍스트 정수의 결정 방법에 관해 기술한다. 먼저, 압축률 향상을 위해 낮은 대비(low contrast)를 적용하는 전처리 과정을 도입한다. 둘째로, 낮은 복잡도(low complexity)를 위해 주목화소와 주변화소 사이의 차분을 양자화하고, 그 값 Q$_1$,Q$_2$, Q$_3$로부터 컨텍스트 정수(Q)의 결정을 위해 우선 순위를 정한 후, 3차원 가상좌표 위로의 할당을 고려한다. 또한, 제안 방법과 JPEG-LS의 near-lossless부분을 비교하여, 다양한 영상에 대하여 적용시켜 본 결과, 제안한 방법의 압축률과 손실이득이 훨씬 좋음을 보인다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.27 no.3A
• /
• pp.211-220
• /
• 2002

In this paper, we propose an efficient algorithm to compress simple computer cell animation at very low bit rate. The structure of proposed algorithm consists of intra frame coding and inter frame coding. In inter frame coding, animation is encoded by color quantization using a palette, rearrangement of index, ADPCM used in JPEG-LS, mapping, classification, and entropy coding. In interframe coding, classifying the characteristics of motion, animation is encoded by block based motion replenishment. Experimental results show that the proposed methods turns out to outperform conventional methods including Flash, FLC, Motion-JPEG, MPEG-1, and MPEG-4.

• ETRI Journal
• /
• v.28 no.2
• /
• pp.260-263
• /
• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2003.11a
• /
• pp.61-64
• /
• 2003

무손실 이미지 압축은 (Lossless Image Compression)은 손실이미지 압축(Lossy Image Compression)에 비해, 압축률(compression ratio)은 떨어지지만, 반면 원이미지와 복원이미지가 완전히 일치하므로, 원인이미지의 품질을 그대로 유지학 수 있다. 따라서, 이미지의 품질(Quality)과 압축효율(compression ratio)은 서로 상반된 관계에 있으며, 지금도 좀 더 놀은 압축효과를 얻으려는 여러 무손실 압축 방법이 발표되고 있다. 무손실 이미지 압축은 이미지의 정확성과 정밀성이 요구되는, 의료영양분야에서 가장 널리 쓰이고 있으며, 그밖에, 원본이미지를 기본으로 다른 이미지프로세싱이 필요한 경우, 압축 복원을 반복적으로 수행할 필요가 있을 때, 기타 사진 예술분야, 원격 영상 등 정밀성이 요구되는 분양에서 쓰이고 있다. [7]. 무손실 이미지 압축의 가장 대표적인 CALIC[3]과 JPEG_LS[2]를 들 수 있다. CALIC은 비교적 높은 압축률을 나타내지만, 3-PASS의 과정을 거치는 복잡도가 지적되고 있다. 반면 JPEG-LS는 압축률은 CALIC에 미치지 못하지만 빠른 코딩/디코딩 속도를 보인다. 본 논문에서는 여거 가지의 예측 모드를 두어, 블록단위별로 주변 CONTEXT에 따라, 최상의 예측 모드를 판단하여, 이를 적용, 픽셀의 여러 값을 최소화하였다. 그 후 적응산술 부호기(Adaptive arithmetc coder)를 이용하여, 인코딩을 하였다. 이때 최대 에러값은 64를 넘지 않게 했으며, 또한 8*8블록별로 에러의 최대값을 측정하여 그 값을 $0\~7$까지의 8개의 대표값으로 양자화하는 방법을 통하여 그에 따라 8개의 보호화 심볼 모델중 알맞은 모델에 적용하였다. 이를 통해, 그 소화값의 확률 구간을 대폭 넓힘으로써, 에러 이미지가 가지고 있는 엔트로피에 좀 근접하게 코딩을 할 수 있게 되었다. 이 방법은 실제로 Arithmetic Coder를 이용하는 다른 압축 방법에 그리고 적용할 수 있다. 실험 결과 압축효율은 JPEG-LS보다 약 $5\%$의 압축 성능 개선이 있었으며, CALIC과는 대등한 압축률을 보이며, 부호화/복호화 속도는 CALIC보다 우수한 것으로 나타났다.

• Journal of KIISE:Software and Applications
• /
• v.37 no.3
• /
• pp.170-176
• /
• 2010

Prediction is an important step in high-performance lossless data compression. In this paper, we propose a novel lossless image coding algorithm to increase prediction accuracy which can display low-resolution images quickly with a multi-resolution image technique. At each resolution, we use pixels of the previous resolution image to estimate current pixel values. For each pixel, we determine its estimated value by considering horizontal, vertical, diagonal edge information and average, weighted-average information obtained from its neighborhood pixels. In the experiment, we show that our method obtains better prediction than JPEG-LS or HINT.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.4
• /
• pp.736-739
• /
• 2009

In this paper, an efficient lossless compression algorithm using motion adaptation is proposed. It is divided into two parts: a motion adaptation based nonlinear predictor part and a residual data coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors using motion adaption. The predictor decides the proper selection of the intra and inter prediction values according to the past prediction error. The reduced error is coded by existing context adaptive coding method. Experimental results show that the proposed algorithm has the higher compression ratio than context modeling methods, such as FELICS, CALIC, and JPEG-LS.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.8
• /
• pp.1497-1504
• /
• 2009

This Paper Propose a method to reduce the calculation time in JPEG2000. That is, if a coefficient is estimate a upper-level subband and its descendents skip the scan process. There is a trade-off relationship between the calculation time and the image quality or the amount of output data, the calculation time and the amount of output data decreases, but the image degradation increases. The experimental results showed that in calculation time was 35% in average, which means that ls ge ses. The ein calculation time and output data can be obtls ed with a cost of an acceptlble image quality degradation.