scispace - formally typeset
Search or ask a question
Proceedings ArticleDOI

Least squares based optimal switched predictors for lossless compression of images

26 Aug 2008-pp 1129-1132
TL;DR: The least-squares (LS) based approach to find optimal predictors for pixels belonging to various slope bins of GAP is presented and results show that the proposed method results in similar performance as that of edge directed prediction (EDP) and Run-length and Adaptive Linear Predictive (RALP) coding.
Abstract: Gradient adjusted predictor (GAP), used in CALIC, consists of seven slope bins and one predictor each is associated with these bins. As the relationship between the predicted pixels and their contexts are complex, these predictors may not be appropriate for prediction of the pixels belonging to the respective slope bins. In this work, we present the least-squares (LS) based approach to find optimal predictors for pixels belonging to various slope bins of GAP. Our simulation results show that the proposed method results in similar performance as that of edge directed prediction (EDP) and Run-length and Adaptive Linear Predictive (RALP) coding. EDP and RALP use symmetrical encoder and decoder structure. On the other hand, we propose an unsymmetrical codec that has higher encoding complexity but decoder is very fast - as fast as a decoder based on GAP principle. However, our encoder is computationally much simpler than an EDP and RALP based encoders.
Citations
More filters
Journal ArticleDOI
TL;DR: A hybrid method by combining geometry-adaptive partitioning and quadtree partitioning to achieve adaptive irregular segmentation for medical images is proposed, which exploits spatial correlation between pixels but it utilizes local structure similarity, resulting in efficient compression performance.
Abstract: To improve the compression rates for lossless compression of medical images, an efficient algorithm, based on irregular segmentation and region-based prediction, is proposed in this paper. Considering that the first step of a region-based compression algorithm is segmentation, this paper proposes a hybrid method by combining geometry-adaptive partitioning and quadtree partitioning to achieve adaptive irregular segmentation for medical images. Then, least square (LS)-based predictors are adaptively designed for each region (regular subblock or irregular subregion). The proposed adaptive algorithm not only exploits spatial correlation between pixels but it utilizes local structure similarity, resulting in efficient compression performance. Experimental results show that the average compression performance of the proposed algorithm is 10.48, 4.86, 3.58, and 0.10% better than that of JPEG 2000, CALIC, EDP, and JPEG-LS, respectively.

18 citations


Cites methods from "Least squares based optimal switche..."

  • ...The LSbased approach was used to find optimal predictors for pixels in GAP [9]....

    [...]

Proceedings ArticleDOI
09 Sep 2010
TL;DR: A least square weight optimization criteria-based prediction scheme, based on the histogram shifting embedding method applied to the image prediction error, is proposed for reducing the prediction error thus improving the embedding performances while guaranteeing high quality of the watermarked image.
Abstract: In this contribution a novel scheme for reversible watermarking of digital images is presented. It is based on the histogram shifting embedding method applied to the image prediction error. A least square weight optimization criteria-based prediction scheme, is proposed for reducing the prediction error thus improving the embedding performances while guaranteeing high quality of the watermarked image. Experimental results shown the effectiveness of the proposed scheme.

8 citations


Cites methods from "Least squares based optimal switche..."

  • ...This optimization technique has been adopted by many authors in lossless image or video compression as in [16] [10]....

    [...]

Journal ArticleDOI
TL;DR: A prediction-based lossless compression algorithm using least square approach is proposed for the compression of CT images and was found to be efficient and tested on DICOM abdomen CT datasets.
Abstract: The storage and transmission of medical data such as CT/MR DICOM images are an essential part of the telemedicine application. In this paper, a prediction-based lossless compression algorithm using least square approach is proposed for the compression of CT images. Prior to compression, the preprocessing was performed by neutrosophic median filter. The gradient adjusted prediction scheme was employed for the determination of prediction coefficients, and polynomial least square fitting approach was used for optimal selection of prediction coefficients. The selected prediction coefficients are finally encoded by Huffman coder for transmission. The quality of the reconstructed image was validated by performance metrics and compared with other compression techniques like JPEG, contextual vector quantization and vector quantization using bat optimization (BAT-VQ). The proposed neutrosophic set-based least square compression algorithm was found to be efficient and tested on DICOM abdomen CT datasets. The hardware implementation was done by Raspberry Pi processor using Java platform for transferring the data through cloud network for telemedicine application.

7 citations

Book ChapterDOI
01 Oct 2014
TL;DR: An additive prediction error expansion (PEE) based reversible data hiding scheme that gives overall low distortion and relatively high embedding capacity and outperforms the state-of-the-art algorithms both in terms of embeddingcapacity and Peak Signal to Noise Ratio.
Abstract: In this paper, we present an additive prediction error expansion (PEE) based reversible data hiding scheme that gives overall low distortion and relatively high embedding capacity. Recently reported interpolation based PEE method uses fixed order predictor that fails to exploit the correlation between the neighborhood pixels and the unknown pixel (to be interpolated). We observed that embedding capacity and distortion of PEE based algorithm depends on the prediction accuracy of the predictor. In view of this observation, we propose an interpolation based method that predicts pixels using predictors of different structure and order. Moreover, we use only original pixels for interpolation. Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art algorithms both in terms of embedding capacity and Peak Signal to Noise Ratio.

7 citations


Cites background or methods from "Least squares based optimal switche..."

  • ...However, predictor structure of [13] consists of only causal pixels whereas proposed predictor structure consists of both causal and non-causal pixels and is described as below: We first find gradients at the unknown pixel (A(n)) in horizontal direction (DH) and in vertical direction (DV ) and then find relative variation as, S = DH − DV (7) where DV = |D(n−4)−B(n−1)|+ |B(n−1)−D(n+2)|+ |D(n−2)−D(n+4)| and DH = |D(n−4)−C(n−3)|+ |C(n−3)−D(n−2)|+ |D(n+2)−D(n+4)|....

    [...]

  • ...For finding prediction coefficients (a), we propose to adopt method given in [13]....

    [...]

  • ...By doing so, we are doing equal treatment to pixels belonging to various bins [13]....

    [...]

Proceedings ArticleDOI
20 May 2012
TL;DR: From performance evaluation, the proposed novel interpolation based prediction scheme is significantly better in terms of compression performance as compared to some of the computationally complex methods.
Abstract: Predictor based algorithms reported in literature uses only causal pixels and hence a non-symmetrical predictor structure for prediction. We observed that the performance of predictor is highly dependent on the predictor structure used. In view of this, we propose a novel interpolation based prediction scheme that enables us to use symmetrical predictor structure. In this sense, we have also used non causal pixels in our scheme. Also, from various interpolation algorithms available, we selected a simple one to ensure decoder simplicity, without any significant loss in performance. From performance evaluation, we found that our algorithm is significantly better in terms of compression performance as compared to some of the computationally complex methods.

6 citations

References
More filters
Journal ArticleDOI
TL;DR: LOCO-I as discussed by the authors is a low complexity projection of the universal context modeling paradigm, matching its modeling unit to a simple coding unit, which is based on a simple fixed context model, which approaches the capability of more complex universal techniques for capturing high-order dependencies.
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 (1966) 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 JPEC-LS.

1,668 citations


"Least squares based optimal switche..." refers background or methods in this paper

  • ...State-of-the-art lossless image compression algorithms, based on predictive coding method, include CALIC [4] and JPEG-LS [5] and these methods use switched predictors for prediction....

    [...]

  • ...Since our work is around GAP frame work, a brief summary of the working principal of GAP is mentioned below, while the same for MED can be found in [5]....

    [...]

  • ...[5] M.J. Weinberger, G. Seroussi, and G. Sapiro, “The LOCO-I Lossless Image Compression Algorithm: Principles and Standardization into JPEG-LS,” HPL-98-193, Nov. 1998....

    [...]

  • ...As a consequence, there are several lossless compression methods available in the present literature [1]-[5]....

    [...]

Journal ArticleDOI
TL;DR: The CALIC obtains higher lossless compression of continuous-tone images than other lossless image coding techniques in the literature and can afford a large number of modeling contexts without suffering from the context dilution problem of insufficient counting statistics as in the latter approach.
Abstract: We propose a context-based, adaptive, lossless image codec (CALIC). The codec obtains higher lossless compression of continuous-tone images than other lossless image coding techniques in the literature. This high coding efficiency is accomplished with relatively low time and space complexities. The CALIC puts heavy emphasis on image data modeling. A unique feature of the CALIC is the use of a large number of modeling contexts (states) to condition a nonlinear predictor and adapt the predictor to varying source statistics. The nonlinear predictor can correct itself via an error feedback mechanism by learning from its mistakes under a given context in the past. In this learning process, the CALIC estimates only the expectation of prediction errors conditioned on a large number of different contexts rather than estimating a large number of conditional error probabilities. The former estimation technique can afford a large number of modeling contexts without suffering from the context dilution problem of insufficient counting statistics as in the latter approach, nor from excessive memory use. The low time and space complexities are also attributed to efficient techniques for forming and quantizing modeling contexts.

1,099 citations


"Least squares based optimal switche..." refers methods in this paper

  • ...State-of-the-art lossless image compression algorithms, based on predictive coding method, include CALIC [4] and JPEG-LS [5] and these methods use switched predictors for prediction....

    [...]

  • ...Since inception of CALIC, many of the researchers used a better, but computationally demanding, prediction scheme to produce better compression ratio than that is achieved by CALIC....

    [...]

  • ...This approach of prediction is computationally efficient and CALIC improves the prediction accuracy further by using a feedback mechanism called bias - cancellation technique....

    [...]

  • ...In this paper, we focus on the Gradient Adjusted Predictor (GAP) used in CALIC and propose to improve its prediction capability (accuracy), with only a small increase in the computational complexity....

    [...]

Journal ArticleDOI
TL;DR: This analysis shows that the superiority of the LS-based adaptation is due to its edge-directed property, which enables the predictor to adapt reasonably well from smooth regions to edge areas.
Abstract: This paper sheds light on the least-square (LS)-based adaptive prediction schemes for lossless compression of natural images. Our analysis shows that the superiority of the LS-based adaptation is due to its edge-directed property, which enables the predictor to adapt reasonably well from smooth regions to edge areas. Recognizing that LS-based adaptation improves the prediction mainly around the edge areas, we propose a novel approach to reduce its computational complexity with negligible performance sacrifice. The lossless image coder built upon the new prediction scheme has achieved noticeably better performance than the state-of-the-art coder CALIC with moderately increased computational complexity.

259 citations


"Least squares based optimal switche..." refers background or result in this paper

  • ...The predictor estimation cost is much lower than that of EDP [2] and RALP [3]....

    [...]

  • ...This is in contrast with the present practice of doing so by finding predictors using characteristics of the local pixels [2]-[3]....

    [...]

Journal ArticleDOI
TL;DR: A switching coding scheme that will combine the advantages of both run-length and adaptive linear predictive coding, and uses a simple yet effective edge detector using only causal pixels for estimating the coding pixels in the proposed encoder.
Abstract: Many coding methods are more efficient with some images than others. In particular, run-length coding is very useful for coding areas of little changes. Adaptive predictive coding achieves high coding efficiency for fast changing areas like edges. In this paper, we propose a switching coding scheme that will combine the advantages of both run-length and adaptive linear predictive coding. For pixels in slowly varying areas, run-length coding is used; otherwise least-squares (LS)-adaptive predictive coding is used. Instead of performing LS adaptation in a pixel-by-pixel manner, we adapt the predictor coefficients only when an edge is detected so that the computational complexity can be significantly reduced. For this, we use a simple yet effective edge detector using only causal pixels. This way, the proposed system can look ahead to determine if the coding pixel is around an edge and initiate the LS adaptation in advance to prevent the occurrence of a large prediction error. With the proposed switching structure, very good prediction results can be obtained in both slowly varying areas and pixels around boundaries. Furthermore, only causal pixels are used for estimating the coding pixels in the proposed encoder; no additional side information needs to be transmitted. Extensive experiments as well as comparisons to existing state-of-the-art predictors and coders will be given to demonstrate its usefulness.

34 citations


"Least squares based optimal switche..." refers background or result in this paper

  • ...For T = 6 and k = 25 (about 35% in [3]) and standard image of size 512×512 involves more than 50 milioins of pixels for the estimation of the covariance matrix....

    [...]

  • ...The predictor estimation cost is much lower than that of EDP [2] and RALP [3]....

    [...]

  • ...This is in contrast with the present practice of doing so by finding predictors using characteristics of the local pixels [2]-[3]....

    [...]

Proceedings ArticleDOI
16 May 2005
TL;DR: This work proposes a statistically valid sixth order predictor, which is used for predicting pixels under various slope conditions in the GAP frame work, and shows that the average entropy of the residual images is reduced significantly, when applied on high resolution images.
Abstract: Modern switched adaptive predictors such as gradient adjusted predictor (GAP) estimates the slope of pixels from the prediction context of a unknown pixel. Based on this slope, the unknown pixels is predicted. But slope alone can not characterize some of the more complex relationship between the predicted pixel and its prediction context. In this work, this complex relationship is found in terms of a statistically valid sixth order predictor, which is used for predicting pixels under various slope conditions in the GAP frame work. It is seen through simulations, that the average entropy of the residual images is reduced significantly, when applied on high resolution images. The computational cost of the proposed method is almost of the same order as that of the GAP and requires the same previous two line buffering while coding.

5 citations


"Least squares based optimal switche..." refers methods in this paper

  • ...GAP [1] classifies pixels in seven classes and it uses a set of seven switched predictors for the prediction....

    [...]

  • ...GAP uses a set of seven switched adaptive predictors [1] and the basic prediction approach using these predictors can be described as given below....

    [...]

  • ...As a consequence, there are several lossless compression methods available in the present literature [1]-[5]....

    [...]