&lt;title&gt;Experiments in lossless and virtually lossless image-compression algorithms&lt;/title&gt;

Langdon, Glen G.; Haidinyak, C.

doi:10.1117/12.204135

Cited by 15 publications

(7 citation statements)

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“…The results in Table II, as well as other comparisons presented in [1], show that LOCO-I/JPEG-LS significantly outperforms other schemes of comparable complexity (e.g., PNG, FELICS, JPEG-Huffman), and it attains compression ratios similar or superior to those of higher complexity schemes based on arithmetic coding (e.g., Sunset CB9 [16], JPEG-Arithmetic). LOCO-I/JPEG-LS is, on the average, within a few percentage points of the best available compression ratios (given, in practice, by CALIC), at a much lower complexity level.…”

Section: Resultsmentioning

confidence: 64%

“…These differences represent the local gradient, thus capturing the level of activity (smoothness, edginess) surrounding a sample, which governs the statistical behavior of prediction errors. Notice that this approach differs from the one adopted in the Sunset family [16] and other schemes, where the context is built out of the prediction errors incurred in previous encodings. By symmetry, 6 , and influence the model in the same way.…”

Section: ) Context Determinationmentioning

confidence: 99%

“…The model in [11], instead, is adaptive not only in terms of the parameter values, but also in structure. While [11] represented the best published compression results at the time (at the cost of high complexity), it could be argued that the improvement over the fixed model structure paradigm, best represented by the Sunset family of algorithms [13]- [16], was scant. The research leading to the CALIC algorithm [17], conducted in parallel to the development of LOCO-I, seems to confirm a pattern of diminishing returns.…”

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confidence: 99%

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The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS

Weinberger

Seroussi

Sapiro

2000

IEEE Trans. on Image Process.

1,368

732

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Abstract-LOCO-I (LOw COmplexity LOssless COmpression for Images) is the algorithm at the core of the new ISO/ITU standard for lossless and near-lossless compression of continuous-tone images, JPEG-LS. It is conceived as a "low complexity projection" of the universal context modeling paradigm, matching its modeling unit to a simple coding unit. By combining simplicity with the compression potential of context models, the algorithm "enjoys the best of both worlds." It is based on a simple fixed context model, which approaches the capability of the more complex universal techniques for capturing high-order dependencies. The model is tuned for efficient performance in conjunction with an extended family of Golomb-type codes, which are adaptively chosen, and an embedded alphabet extension for coding of low-entropy image regions. LOCO-I attains compression ratios similar or superior to those obtained with state-of-the-art schemes based on arithmetic coding. Moreover, it is within a few percentage points of the best available compression ratios, at a much lower complexity level. We discuss the principles underlying the design of LOCO-I, and its standardization into JPEG-LS.

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Section: Resultsmentioning

confidence: 64%

Section: ) Context Determinationmentioning

confidence: 99%

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confidence: 99%

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The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS

Weinberger

Seroussi

Sapiro

2000

IEEE Trans. on Image Process.

1,368

732

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“…While UCM provided the best published compression results at the time (at the cost of high complexity), it could be argued that the improvement over the fixed model structure paradigm, best represented by the Sunset family of algorithms (further developed in [21] and [22]), was scant. However, the image modeling principles outlined in [53] shed light on the workings of some of the leading lossless image compression algorithms.…”

Section: Modeling For High Performance Compression With Arithmetimentioning

confidence: 99%

Lossless compression of continuous-tone images

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“…4. ROT is coded near-losslessly, with no rate control, but the overall image undergoes rate-controlled image compression.…”

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Rate-controlled, region-of-interest-based image coding with JPEG-LS

Edirisinghe

Bedi

2003

SPIE Proceedings

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Since the standardization of JPEG-LS, several improvements and variations to the original algorithms have been proposed. In this paper we propose a Region of Interest (ROT) based coding strategy for JPEG-LS that has the additional ability of providing effective rate controlled image compression. Given a single ROT or multiple ROTs of a fixed or arbitrary shape, the scheme we propose is able to compress a given image by a required ratio, whilst maintaining the subjective image of the ROTs at either lossless or at a quality specified by a Target Compression Ratio ( TCR) of the ROT. We provide experimental results to compare the performance of the proposed rate-control algorithm with the state of the art near lossless rate control schemes. We show that the proposed scheme is able to achieve much higher TCRs, at increased accuracy and better objective image quality, using a less computationally intensive rate control algorithm. Finally we demonstrate that the proposed ROT based coding scheme can be used to extend the applicability of JPEG-LS to medical and satellite imaging applications and provides a useful alternative to JPEG-2000 based ROT coding.

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<title>Experiments in lossless and virtually lossless image-compression algorithms</title>

Cited by 15 publications

References 0 publications

The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS

The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS

Lossless compression of continuous-tone images

Rate-controlled, region-of-interest-based image coding with JPEG-LS

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