A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

Fractal compression is the lossy compression technique in the field of gray/color image and video compression. It gives high compression ratio, better image quality with fast decoding time but improvement in encoding time is a challenge. This review paper/article presents the analysis of most significant existing approaches in the field of fractal based gray/color images and video compression, different block matching motion estimation approaches for finding out the motion vectors in a frame based on inter-frame coding and intra-frame coding i.e. individual frame coding and automata theory based coding approaches to represent an image/sequence of images. Though different review papers exist related to fractal coding, this paper is different in many sense. One can develop the new shape pattern for motion estimation and modify the existing block matching motion estimation with automata coding to explore the fractal compression technique with specific focus on reducing the encoding time and achieving better image/video reconstruction quality. This paper is useful for the beginners in the domain of video compression

An Investigation of Block Searching Algorithms for Video Frame Codecs

Block matching is the most computationally demanding aspect of the video encoding process. In many applications real-time video encoding is desired and therefore it is important that the encoding is fast. Also where handheld devices such as a PDA or mobile phone are concerned a less computationally intensive algorithm means a simpler processor can be used which saves on hardware costs and also extends battery life. An optimised algorithm also allows these devices to be used in low bandwidth wireless networks. The challenge is to decrease the computational load on the system without compromising the quality of the video stream too much, thus enabling easier and less expensive implementations of real-time encoding. This thesis appraises some of the principal Block Search Algorithms used in Video compression today. This work follows on from the work of Aroh Barjatya who implemented 7 common Block Search Algorithms to predict P-frames in MATLAB. Three further hybrid DS algorithms are implemented in MATLAB. Additional code is added to produce plots of the main metrics and to calculate some statistics such as Average Searching Points, Average PSNR and the Speed Improvement Ratio with respect to the Diamond Search and the Exhaustive Search. For a comparative analysis with previous studies 3 standard industry test sequences are used. The first sequence, Miss America is a typical videoconferencing scene with limited object motion and a stationary background. The second sequence, Flower Garden consists mainly of stationary objects, but with a fast camera panning motion. The third sequence, Football contains large local object motion. The performance of the 3 implemented algorithms were assessed by the aforementioned statistics. Simulation results showed that the NCDS was the fastest algorithm amongst the 3 hybrid DS algorithms simulated. A speedup ranging from 10% for the complex motion sequence Flower Garden to nearly 54% for the low motion video conferencing sequence Miss America was recorded. All 3 algorithms performed very competitively in terms of PSNR compared to the DS even though they use a lower number of search points on average. It was shown that the NCDS has marginally worse PSNR performance than the DS compared to the other 2 algorithms – the highest being a drop in PSNR of 0.680dB for the Flower Garden sequence. However, the speed improvements for NCDS are quite substantial and thus would justify its use over the DS. The results from the implementation concurred with the literature therefore validating the implementation. The implementation was used as a guide in nominating a ‘robust’ Block Search Algorithm. When the DS, CDS, SCDS and the NCDS were compared with ARPS it was shown that ARPS generally gave both higher PSNR and higher search speed for all 3 sequences. The reason for the good performance of ARPS is that it quickly directs the search into the local region of the global minimum by calculating the Predicted Motion Vector. The minimum error from a rood pattern of nodes is found and then a final refined search calculates the motion vector. Simulation results showed that ARPS was the best algorithm amongst the 10 algorithms simulated from the point of view of speed (lowest number of search points used per macroblock) and video quality (PSNR). For real-time encoding of video the best fast block motion algorithm to advise is ARPS

Research and developments of Dirac video codec

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.In digital video compression, apart from storage, successful transmission of the compressed video data over the bandwidth limited erroneous channels is another important issue. To enable a video codec for broadcasting application, it is required to implement the corresponding coding tools (e.g. error-resilient coding, rate control etc.). They are normally non-normative parts of a video codec and hence their specifications are not defined in the standard. In Dirac as well, the original codec is optimized for storage purpose only and so, several non-normative part of the encoding tools are still required in order to be able to use in other types of application. Being the "Research and Developments of the Dirac Video Codec" as the research title, phase I of the project is mainly focused on the error-resilient transmission over a noisy channel. The error-resilient coding method used here is a simple and low complex coding scheme which provides the error-resilient transmission of the compressed video bitstream of Dirac video encoder over the packet erasure wired network. The scheme combines source and channel coding approach where error-resilient source coding is achieved by data partitioning in the wavelet transformed domain and channel coding is achieved through the application of either Rate-Compatible Punctured Convolutional (RCPC) Code or Turbo Code (TC) using un-equal error protection between header plus MV and data. The scheme is designed mainly for the packet-erasure channel, i.e. targeted for the Internet broadcasting application. But, for a bandwidth limited channel, it is still required to limit the amount of bits generated from the encoder depending on the available bandwidth in addition to the error-resilient coding. So, in the 2nd phase of the project, a rate control algorithm is presented. The algorithm is based upon the Quality Factor (QF) optimization method where QF of the encoded video is adaptively changing in order to achieve average bitrate which is constant over each Group of Picture (GOP). A relation between the bitrate, R and the QF, which is called Rate-QF (R-QF) model is derived in order to estimate the optimum QF of the current encoding frame for a given target bitrate, R. In some applications like video conferencing, real-time encoding and decoding with minimum delay is crucial, but, the ability to do real-time encoding/decoding is largely determined by the complexity of the encoder/decoder. As we all know that motion estimation process inside the encoder is the most time consuming stage. So, reducing the complexity of the motion estimation stage will certainly give one step closer to the real-time application. So, as a partial contribution toward realtime application, in the final phase of the research, a fast Motion Estimation (ME) strategy is designed and implemented. It is the combination of modified adaptive search plus semi-hierarchical way of motion estimation. The same strategy was implemented in both Dirac and H.264 in order to investigate its performance on different codecs. Together with this fast ME strategy, a method which is called partial cost function calculation in order to further reduce down the computational load of the cost function calculation was presented. The calculation is based upon the pre-defined set of patterns which were chosen in such a way that they have as much maximum coverage as possible over the whole block. In summary, this research work has contributed to the error-resilient transmission of compressed bitstreams of Dirac video encoder over a bandwidth limited error prone channel. In addition to this, the final phase of the research has partially contributed toward the real-time application of the Dirac video codec by implementing a fast motion estimation strategy together with partial cost function calculation idea.BBC R&D and Brunel University

Fast and Efficient Foveated Video Compression Schemes for H.264/AVC Platform

Some fast and efficient foveated video compression schemes for H.264/AVC platform are presented in this dissertation. The exponential growth in networking technologies and widespread use of video content based multimedia information over internet for mass communication applications like social networking, e-commerce and education have promoted the development of video coding to a great extent. Recently, foveated imaging based image or video compression schemes are in high demand, as they not only match with the perception of human visual system (HVS), but also yield higher compression ratio. The important or salient regions are compressed with higher visual quality while the non-salient regions are compressed with higher compression ratio. From amongst the foveated video compression developments during the last few years, it is observed that saliency detection based foveated schemes are the keen areas of intense research. Keeping this in mind, we propose two multi-scale saliency detection schemes. (1) Multi-scale phase spectrum based saliency detection (FTPBSD); (2) Sign-DCT multi-scale pseudo-phase spectrum based saliency detection (SDCTPBSD). In FTPBSD scheme, a saliency map is determined using phase spectrum of a given image/video with unity magnitude spectrum. On the other hand, the proposed SDCTPBSD method uses sign information of discrete cosine transform (DCT) also known as sign-DCT (SDCT). It resembles the response of receptive field neurons of HVS. A bottom-up spatio-temporal saliency map is obtained by linear weighted sum of spatial saliency map and temporal saliency map. Based on these saliency detection techniques, foveated video compression (FVC) schemes (FVC-FTPBSD and FVC-SDCTPBSD) are developed to improve the compression performance further.Moreover, the 2D-discrete cosine transform (2D-DCT) is widely used in various video coding standards for block based transformation of spatial data. However, for directional featured blocks, 2D-DCT offers sub-optimal performance and may not able to efficiently represent video data with fewer coefficients that deteriorates compression ratio. Various directional transform schemes are proposed in literature for efficiently encoding such directional featured blocks. However, it is observed that these directional transform schemes suffer from many issues like ‘mean weighting defect’, use of a large number of DCTs and a number of scanning patterns. We propose a directional transform scheme based on direction-adaptive fixed length discrete cosine transform (DAFL-DCT) for intra-, and inter-frame to achieve higher coding efficiency in case of directional featured blocks.Furthermore, the proposed DAFL-DCT has the following two encoding modes. (1) Direction-adaptive fixed length ― high efficiency (DAFL-HE) mode for higher compression performance; (2) Direction-adaptive fixed length ― low complexity (DAFL-LC) mode for low complexity with a fair compression ratio. On the other hand, motion estimation (ME) exploits temporal correlation between video frames and yields significant improvement in compression ratio while sustaining high visual quality in video coding. Block-matching motion estimation (BMME) is the most popular approach due to its simplicity and efficiency. However, the real-world video sequences may contain slow, medium and/or fast motion activities. Further, a single search pattern does not prove efficient in finding best matched block for all motion types. In addition, it is observed that most of the BMME schemes are based on uni-modal error surface. Nevertheless, real-world video sequences may exhibit a large number of local minima available within a search window and thus possess multi-modal error surface (MES). Hence, the following two uni-modal error surface based and multi-modal error surface based motion estimation schemes are developed. (1) Direction-adaptive motion estimation (DAME) scheme; (2) Pattern-based modified particle swarm optimization motion estimation (PMPSO-ME) scheme. Subsequently, various fast and efficient foveated video compression schemes are developed with combination of these schemes to improve the video coding performance further while maintaining high visual quality to salient regions. All schemes are incorporated into the H.264/AVC video coding platform. Various experiments have been carried out on H.264/AVC joint model reference software (version JM 18.6). Computing various benchmark metrics, the proposed schemes are compared with other existing competitive schemes in terms of rate-distortion curves, Bjontegaard metrics (BD-PSNR, BD-SSIM and BD-bitrate), encoding time, number of search points and subjective evaluation to derive an overall conclusion

Robustness and Accuracy of Feature-Based Single Image 2-D–3-D Registration Without Correspondences for Image-Guided Intervention

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Scalable light field representation and coding

This Thesis aims to advance the state-of-the-art in light field representation and coding. In this context, proposals to improve functionalities like light field random access and scalability are also presented. As the light field representation constrains the coding approach to be used, several light field coding techniques to exploit the inherent characteristics of the most popular types of light field representations are proposed and studied, which are normally based on micro-images or sub-aperture-images. To encode micro-images, two solutions are proposed, aiming to exploit the redundancy between neighboring micro-images using a high order prediction model, where the model parameters are either explicitly transmitted or inferred at the decoder, respectively. In both cases, the proposed solutions are able to outperform low order prediction solutions. To encode sub-aperture-images, an HEVC-based solution that exploits their inherent intra and inter redundancies is proposed. In this case, the light field image is encoded as a pseudo video sequence, where the scanning order is signaled, allowing the encoder and decoder to optimize the reference picture lists to improve coding efficiency. A novel hybrid light field representation coding approach is also proposed, by exploiting the combined use of both micro-image and sub-aperture-image representation types, instead of using each representation individually. In order to aid the fast deployment of the light field technology, this Thesis also proposes scalable coding and representation approaches that enable adequate compatibility with legacy displays (e.g., 2D, stereoscopic or multiview) and with future light field displays, while maintaining high coding efficiency. Additionally, viewpoint random access, allowing to improve the light field navigation and to reduce the decoding delay, is also enabled with a flexible trade-off between coding efficiency and viewpoint random access.Esta Tese tem como objetivo avançar o estado da arte em representação e codificação de campos de luz. Neste contexto, são também apresentadas propostas para melhorar funcionalidades como o acesso aleatório ao campo de luz e a escalabilidade. Como a representação do campo de luz limita a abordagem de codificação a ser utilizada, são propostas e estudadas várias técnicas de codificação de campos de luz para explorar as características inerentes aos seus tipos mais populares de representação, que são normalmente baseadas em micro-imagens ou imagens de sub-abertura. Para codificar as micro-imagens, são propostas duas soluções, visando explorar a redundância entre micro-imagens vizinhas utilizando um modelo de predição de alta ordem, onde os parâmetros do modelo são explicitamente transmitidos ou inferidos no decodificador, respetivamente. Em ambos os casos, as soluções propostas são capazes de superar as soluções de predição de baixa ordem. Para codificar imagens de sub-abertura, é proposta uma solução baseada em HEVC que explora a inerente redundância intra e inter deste tipo de imagens. Neste caso, a imagem do campo de luz é codificada como uma pseudo-sequência de vídeo, onde a ordem de varrimento é sinalizada, permitindo ao codificador e decodificador otimizar as listas de imagens de referência para melhorar a eficiência da codificação. Também é proposta uma nova abordagem de codificação baseada na representação híbrida do campo de luz, explorando o uso combinado dos tipos de representação de micro-imagem e sub-imagem, em vez de usar cada representação individualmente. A fim de facilitar a rápida implantação da tecnologia de campo de luz, esta Tese também propõe abordagens escaláveis de codificação e representação que permitem uma compatibilidade adequada com monitores tradicionais (e.g., 2D, estereoscópicos ou multivista) e com futuros monitores de campo de luz, mantendo ao mesmo tempo uma alta eficiência de codificação. Além disso, o acesso aleatório de pontos de vista, permitindo melhorar a navegação no campo de luz e reduzir o atraso na descodificação, também é permitido com um equilíbrio flexível entre eficiência de codificação e acesso aleatório de pontos de vista

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task