Development and comparison of transforms for prediction residuals of markov-process-based intra prediction

Download

index.pdf

Date

2014

Author

Tekeli, Nihat

Metadata

Show full item record

Item Usage Stats

181
views

68
downloads

Intra prediction is an important tool used in modern intra-frame coding. In intra prediction, a block of pixels are predicted from previously reconstructed neighbor pixels of the block by copying the previously reconstructed neighbor pixels of the block along an angular direction inside the block. The prediction residual block is then transformed with the conventional 2-D Discrete Cosine Transform (DCT). Recently, it has been shown that transforming the intra prediction residuals with an Asymmetric Discrete Sine Transform (ADST) along the prediction direction and the well-known DCT along the perpendicular direction improves the compression performance. More recently, a recursive intra prediction algorithm, obtained by modeling image blocks with 2-D Markov processes, is proposed to improve the conventional copyingbased intra prediction methods. In this thesis, we develop transforms for the intra prediction residuals obtained with these new recursive intra prediction algorithms. Using the 2-D Markov process correlations of each intra prediction mode, we obtain the correlations of the prediction residuals, and numerically compute Karhunen Loeve Transforms (KLT) for each intra prediction mode. We present compression results to compare the derived transforms with the conventional 2-D DCT and the hybrid ADST/DCT within the H.264 reference software.

Subject Keywords

Image processing., İmage compression., Video compression., Markov processes.

URI

http://etd.lib.metu.edu.tr/upload/12616776/index.pdf
https://hdl.handle.net/11511/23277

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

INTRA PREDICTION BASED ON STATISTICAL MODELING OF IMAGES Kamışlı, Fatih (2012-11-30) Intra prediction is an important part of intra-frame coding. A number of approaches have been proposed to improve intra prediction including a general linear prediction approach in which a weighted sum of all available neighbor pixels is used to predict each block pixel. An important part of this approach is the determination of the used weights. One method to determine the weights is to use the least-squares solution of an overdetermined linear system of weights. In this paper, we present an alternative ap...
Improved state estimation for jump Markov linear systems Orguner, Umut; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2005) This thesis presents a comprehensive example framework on how current multiple model state estimation algorithms for jump Markov linear systems can be improved. The possible improvements are categorized as: -Design of multiple model state estimation algorithms using new criteria. -Improvements obtained using existing multiple model state estimation algorithms. In the first category, risk-sensitive estimation is proposed for jump Markov linear systems. Two types of cost functions namely, the instantaneous an...
UTILIZATION OF SPATIAL INFORMATION FOR POINT CLOUD SEGMENTATION Akman, Oytun; Bayramoglu, Neslihan; Alatan, Abdullah Aydın; Jonker, Pieter (2010-06-09) Object segmentation has an important role in the field of computer vision for semantic information inference. Many applications such as 3DTV archive systems, 3D/2D model fitting, object recognition and shape retrieval are strongly dependent to the performance of the segmentation process. In this paper we present a new algorithm for object localization and segmentation based on the spatial information obtained via a Time-of-Flight (TOF) camera. 3D points obtained via a TOF camera are projected onto the major...
Improved Knowledge Distillation with Dynamic Network Pruning Şener, Eren; Akbaş, Emre (2022-9-30) Deploying convolutional neural networks to mobile or embedded devices is often prohibited by limited memory and computational resources. This is particularly problematic for the most successful networks, which tend to be very large and require long inference times. Many alternative approaches have been developed for compressing neural networks based on pruning, regularization, quantization or distillation. In this paper, we propose the “Knowledge Distillation with Dynamic Pruning” (KDDP), which trains a dyn...
The Role of Mathematics in the Design Process Under the Influence of Computational and Design Technologies Sorguç, Arzu (null; 2006-06-07) In the design process today, the use of computational and information technologies demands a new way of thinking: “algorithmic thinking“. The first generation of computera-aided design tools have been replaced by highly sophisticated design tools used not only in design but also in construction and product life. These revolutionary step consists in designing directly in 3-D instead of designing by sections and planes. But are computers and new technologies really employed in design process or simply as a ne...

Citation Formats

N. Tekeli, “Development and comparison of transforms for prediction residuals of markov-process-based intra prediction,” M.S. - Master of Science, Middle East Technical University, 2014.