Reversible compression of HDTV images using median adaptive prediction and arithmetic coding

Martucci, S.A.

doi:10.1109/iscas.1990.112371

Cited by 96 publications

(28 citation statements)

References 3 publications

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“…This expresses the expected smoothness of the image in the absence of edges. The predictor (1) has been used in image compression applications [37], under a different interpretation: The guessed value is seen as the median of three fixed predictors, , and . Combining both interpretations, this predictor was renamed during the standardization process "median edge detector" (MED).…”

Section: A Predictionmentioning

confidence: 99%

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: A Predictionmentioning

confidence: 99%

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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show abstract

“…In principle, the approach of [8] is used with a small modification. Firstly, the frame is converted into a prediction residual using the median adaptive prediction (MAP) [13]. This simulates the fact that, in HEVC, the colour transform is applied to the prediction error.…”

Section: Implementation Detailsmentioning

confidence: 99%

Adaptive colour-space selection in high efficiency video coding

Strutz

Leipnitz

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Recent developments in the standardisation of High Efficiency Video Coding (HEVC) have shown that the block-wise activation/deactivation of a colour transform can significantly improve the compression performance. This coding tool is based on a fixed colour space which is either YCgCo in lossy compression mode or YCgCo-R in the lossless mode.The proposed method shows that the performance can be increased even more when the colour space is not fixed but selected dependent on the image characteristic. Improvements of more than 2% can be achieved in lossless intra coding if the colour space is automatically chosen once for the entire image. In lossy intra compression, the performance can also be increased if a proper colour space is chosen.

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“…The same predictor was also considered as the median of three simple linear predictors: x t , x r , and x t + x r − x tr [33], that is,ŷ = 2x t +2x r −x tr 3 . Comparing with causal prediction ways, noncausal prediction approaches can improve the prediction precision by using more neighboring samples.…”

Section: Image Predictors For Reversible Watermarkingmentioning

confidence: 99%

“…6b that the difference values are always positive, indicating effect of the rounding operation and prediction with modified pixels on the standard deviations. Figures 5 and 6 show that the prediction errors with the proposed predictor Furthermore, Table 1 lists the absolute mean values and the standard deviations of four benchmark images predicted with five different predictors (difference predictor used in [9,10], integer MED predictor used in [14,18], non-integer MED predictor [33], the prediction method in [15], and the proposed one in this paper). We can see from this table that the prediction method proposed in this paper can provide the smallest mean values and standard deviations.…”

Section: Comparison Of Typical Predictorsmentioning

confidence: 99%

Non-integer expansion embedding techniques for reversible image watermarking

Xiang

Wang

2015

EURASIP J. Adv. Signal Process.

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This work aims at reducing the embedding distortion of prediction-error expansion (PE)-based reversible watermarking. In the classical PE embedding method proposed by Thodi and Rodriguez, the predicted value is rounded to integer number for integer prediction-error expansion (IPE) embedding. The rounding operation makes a constraint on a predictor's performance. In this paper, we propose a non-integer PE (NIPE) embedding approach, which can proceed non-integer prediction errors for embedding data into an audio or image file by only expanding integer element of a prediction error while keeping its fractional element unchanged. The advantage of the NIPE embedding technique is that the NIPE technique can really bring a predictor into full play by estimating a sample/pixel in a noncausal way in a single pass since there is no rounding operation. A new noncausal image prediction method to estimate a pixel with four immediate pixels in a single pass is included in the proposed scheme. The proposed noncausal image predictor can provide better performance than Sachnev et al.'s noncausal double-set prediction method (where data prediction in two passes brings a distortion problem due to the fact that half of the pixels were predicted with the watermarked pixels). In comparison with existing several state-of-the-art works, experimental results have shown that the NIPE technique with the new noncausal prediction strategy can reduce the embedding distortion for the same embedding payload.

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Reversible compression of HDTV images using median adaptive prediction and arithmetic coding

Cited by 96 publications

References 3 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

Adaptive colour-space selection in high efficiency video coding

Non-integer expansion embedding techniques for reversible image watermarking

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