Sérgio M. M. de Faria

Scanned Compound Document Encoding Using Multiscale Recurrent Patterns

In this paper, we propose a new encoder for scanned compound documents, based upon a recently introduced coding paradigm called multidimensional multiscale parser (MMP). MMP uses approximate pattern matching, with adaptive multiscale dictionaries that contain concatenations of scaled versions of previously encoded image blocks. These features give MMP the ability to adjust to the input images characteristics, resulting in high coding efficiencies for a wide range of image types. This versatility makes MMP a good candidate for compound digital document encoding. The proposed algorithm first classifies the image blocks as smooth (texture) and nonsmooth (text and graphics). Smooth and nonsmooth blocks are then compressed using different MMP-based encoders, adapted for encoding either type of blocks. The adaptive use of these two types of encoders resulted in performance gains over the original MMP algorithm, further increasing the performance advantage over the current state-of-the-art image encoders for scanned compound images, without compromising the performance for other image types.

Improving multiscale recurrent pattern image coding with least-squares prediction mode

The Multidimensional Multiscale Parser-based (MMP) image coding algorithm, when combined with flexible partitioning and predictive coding techniques (MMP-FP), provides state-of-the-art performance. In this paper we investigate the use of adaptive least-squares prediction in MMP. The linear prediction coefficients implicitly embed the local texture characteristics, and are computed based on a blocks causal neighborhood (composed of already reconstructed data). Thus, the intra prediction mode is adaptively adjusted according to the local context and no extra overhead is needed for signaling the coefficients. We add this new context-adaptive linear prediction mode to the other MMP prediction modes, that are based on the ones used in H.264/AVC; the best mode is chosen through rate-distortion optimization. Simulation results show that least-squares prediction is able to significantly increase MMP-FPs rate-distortion performance for smooth images, leading to better results than the ones of state-of-theart, transform-based methods. Yet with the addition of least-squares prediction MMP-FP presents no performance loss when used for encoding non-smooth images, such as text and graphics.

Light field HEVC-based image coding using locally linear embedding and self-similarity compensated prediction

Light field imaging is a promising new technology that allows the user not only to change the focus and perspective after taking a picture, as well as to generate 3D content, among other applications. However, light field images are characterized by large amounts of data and there is a lack of coding tools to efficiently encode this type of content. Therefore, this paper proposes the addition of two new prediction tools to the HEVC framework, to improve its coding efficiency. The first tool is based on the local linear embedding-based prediction and the second one is based on the self-similarity compensated prediction. Experimental results show improvements over JPEG and HEVC in terms of average bitrate savings of 71.44% and 31.87%, and average PSNR gains of 4.73dB and 0.89dB, respectively.

Intra-prediction for color image coding using YUV correlation

In this paper we present a new algorithm for chroma prediction in YUV images, based on inter component correlation. Despite the YUV color space transformation for inter component decorrelation, some dependency still exists between the Y, U and V chroma components. This dependency has been previously used to predict the chrominance data from the reconstructed luminance. In this paper we show that a chrominance component can be more efficiently predicted by using the reconstructed data from both the luminance and the remaining chrominance signal. The proposed chroma prediction is implemented and tested using the Multidimensional Multiscale Parser (MMP) image encoding algorithm. It is shown that the new color prediction mode outperforms the originally proposed prediction methods. Furthermore, by using the new color prediction scheme, MMP is consistently better than the state-of-the-art H.264/AVC for coding both for the luminance and the chrominance image components.

A generic post-deblocking filter for block based image compression algorithms

In this paper we propose a new post-processing deblocking technique that is independent of the compression method used to encode the image. The development of this filter was motivated by the use of Multidimensional Multiscale Parser (MMP) algorithm, a generic lossy and lossless compression method. Since it employs an adaptive block size, it presents some impairments when using the deblocking techniques presented in the literature. This led us to the development of a new and more generic deblocking method, based on total variation and adaptive bilateral filtering. The proposed method was evaluated not only for still images, but also for video sequences, encoded using pattern matching and transform based compression methods. For all cases, both the objective and subjective quality of the reconstructed images were improved, showing the versatility of the proposed technique.

Intra Predictive Depth Map Coding Using Flexible Block Partitioning

A complete encoding solution for efficient intra-based depth map compression is proposed in this paper. The algorithm, denominated predictive depth coding (PDC), was specifically developed to efficiently represent the characteristics of depth maps, mostly composed by smooth areas delimited by sharp edges. At its core, PDC involves a directional intra prediction framework and a straightforward residue coding method, combined with an optimized flexible block partitioning scheme. In order to improve the algorithm in the presence of depth edges that cannot be efficiently predicted by the directional modes, a constrained depth modeling mode, based on explicit edge representation, was developed. For residue coding, a simple and low complexity approach was investigated, using constant and linear residue modeling, depending on the prediction mode. The performance of the proposed intra depth map coding approach was evaluated based on the quality of the synthesized views using the encoded depth maps and original texture views. The experimental tests based on all intra configuration demonstrated the superior rate-distortion performance of PDC, with average bitrate savings of 6%, when compared with the current state-of-the-art intra depth map coding solution present in the 3D extension of a high-efficiency video coding (3D-HEVC) standard. By using view synthesis optimization in both PDC and 3D-HEVC encoders, the average bitrate savings increase to 14.3%. This suggests that the proposed method, without using transform-based residue coding, is an efficient alternative to the current 3D-HEVC algorithm for intra depth map coding.

Mobile web server for elderly people monitoring

In this paper we propose a mobile system for monitoring of moving objects, namely tracking elderly people. This system aims to provide help for people with some kind of memory loss disease, namely Alzheimerpsilas. It is capable of providing the geographic position of the person carrying the mobile equipment, both by a patient request (pressing a key to send a message) or anytime trough a webpage consult by an external authorized person. The portable device consists of a GSM/GPRS module, a GPS module, a I/O and MCU module and a web server. It also incorporates hands free voice communication capability, which allows communication with a distant person, in the event of an unexpected incident. The problem of external web server dependency is tackled by implementing an embedded web server in the mobile device. This significantly reduces the user expenses that are limited to the data communication between any authorized person and the mobile system. Additionally, we have included a tri-axial accelerometer sensor to constrain the current consumption while the device is not moving, which can also detect the falling of the patient. However, the main achievement of this work, regardless the hardware integration, is the development of a web server supported on the relatively limited computational resources available in the module. To this extent, it is not required any dedicated software to access this equipment, but a web browser.

Improving H.264/AVC Inter Compression with Multiscale Recurrent Patterns

In this paper we describe the ongoing work on a new paradigm for compressing the motion predicted error in a video coder, referred to as MMP-Video. This new coding algorithm uses the multidimensional multiscale parser image coding algorithm to encode the residue error, in a H.264/AVC based video coder. MMP has shown to perform very well as a universal still image coding method, particularly when it is combined with intra prediction schemes. In addition, previously published preliminary results have also presented MMP as a promising video coding method. In this paper, we propose new dictionary updating techniques for MMP-video. Along with other functional optimizations, these techniques allow for a significant improvement in the encoder performance. Thus, we were able to achieve considerable gains over H.264/AVC for B slices, specially for medium and high bit-rates, while maintaining equivalent performance for the P slices.

Video transcoding from H.264/AVC to MPEG-2 with reduced computational complexity

This paper addresses video transcoding from H.264/AVC into MPEG-2 with reduced complexity and high rate-distortion efficiency. While the overall concept is based on a cascaded decoder-encoder, the novel adaptation methods developed in this work have the advantage of providing very good performance in H.264/AVC to MPEG-2 transcoding. The proposed approach exploits the similarities between the coding tools used in both standards, with the objective of obtaining a computationally efficient transcoder without penalising the signal quality. Fast and efficient methods are devised for conversion of macroblock coding modes and translation of motion information in order to compute the MPEG-2 coding format with a reduced number of operations, by reusing the corresponding data embedded in the incoming H.264/AVC coded stream. In comparison with a cascaded decoder-encoder, the fast transcoder achieves computational complexity savings up to 60% with slightly better peak signal-to-noise ratio (PSNR) at the same bitrate.

Contributions to lossless coding of medical images using minimum rate predictors

Medical imaging compression is experiencing a growth in terms of usage and image resolution, namely in diagnostics systems that require a large set of images, like MRI or CT. Furthermore, legal and diagnosis restrictions impose the use of lossless compression and data archival for several years. These facts create a demand for more efficient compression tools, used for archiving and communication. In this work, we first evaluate the performance of traditional medical image compression algorithms against that of recent state of the art lossless image encoders. We then propose a method to improve the Minimum Rate Predictors lossless encoder, by exploiting inter picture redundancy in volumetric anatomical images. Results show that the proposed method is more efficient than state of the art encoders, such as HEVC, by about 28.8%, and achieves a gain of up to 57.8% in compression ratio when compared with traditional methods.