Edge-adaptive spatial video de-interlacing algorithms based on fuzzy logic

Since the human visual system is especially sensitive to image edges, edge-dependent spatial interpolators have been proposed in literature as a means of successfully restoring edges while avoiding the staircase effect of linear spatial algorithms. This paper addresses the application of video de-interlacing, which constitutes an indispensable stage in video format conversion. Classic edge-adaptive de-interlacing algorithms introduce annoying artifacts when the edge directions are evaluated incorrectly. This paper presents two ways of exploiting fuzzy reasoning to reinforce edges without an excessive increase in computational complexity. The performance of the proposed algorithms is analyzed by de-interlacing a wide set of test sequences. The study compares the two proposals both with each other and with other edge-adaptive de-interlacing methods reported in the recent literatur

An improved algorithm for deinterlacing video streams

The MPEG-4 standard for computerized video incorporates the concept of a video object pLane While in the simplest case this can be the full rectangular frame, the standard supports a hierarchical set of arbitrary shaped planes, one for each content sensitive video object. Herein is proposed a method for extracting arbitrary planes from video that does not already contain video object plane information; Deinterlacing is the process of taking two video fields, each at half the height of the finalized image frame, and combining them into that finalized frame. As the fields are not captured simultaneously, temporal artifacts may result. Herein is proposed a method to use the above mentioned video object planes to calculate the intra-field motion of objects in the video stream and correct for such motion leading to a higher quality deinterlaced output.*; *This dissertation is a compound document (contains both a paper copy and a CD as part of the dissertation)

Fuzzy logic-based embedded system for video de-interlacing

Video de-interlacing algorithms perform a crucial task in video processing. Despite these algorithms are developed using software implementations, their implementations in hardware are required to achieve real-time operation. This paper describes the development of an embedded system for video de-interlacing. The algorithm for video de-interlacing uses three fuzzy logic-based systems to tackle three relevant features in video sequences: motion, edges, and picture repetition. The proposed strategy implements the algorithm as a hardware IP core on a FPGA-based embedded system. The paper details the proposed architecture and the design methodology to develop it. The resulting embedded system is verified on a FPGA development board and it is able to de-interlace in real-tim

Fuzzy motion adaptive algorithm and its hardware implementation for video de-interlacing

Interlacing techniques were introduced in the early analog TV transmission systems as an efficient mechanism capable of halving the video bandwidth. Currently, interlacing is also used by some modern digital TV transmission systems, however, there is a problem at the receiver side since the majority of modern display devices require a progressive scanning. De-interlacing algorithms convert an interlaced video signal into a progressive one by performing interpolation. To achieve good de-interlacing results, dynamical and local image features should be considered. The gradual adaptation of the de-interlacing technique as a function of the level of motion detected in each pixel is a powerful method that can be carried out by means of fuzzy inference. The starting point of our study is an algorithm that uses a fuzzy inference system to evaluate motion locally (FMA algorithm). Our approach is based on convolution techniques to process a fuzzy rulebase for motion-adaptive de-interlacing. Different strategies based on bi-dimensional convolution techniques are proposed. In particular, the algorithm called 'single convolution algorithm' introduces significant advantages: a more accurate measurement of the level of motion using a matrix of weights, and a unique fuzzification process after the global estimation, which reduces the computational cost. Different architectures for the hardware implementation of this algorithm are described in VHDL language. The physical realization is carried out on a RC100 Celoxica FPGA development board. © 2010 Elsevier B.V.Comunidad Europea FP7-INFSO-ICT-248858Gobierno de España TIN2005-08943-C02-01 y TEC2008-04920Junta de Andalucía P08-TIC-0367

Tuning of a hierarchical fuzzy system for video de-interlacing

The tuning of hierarchical fuzzy systems are not supported by the majority of CAD tools available at the market currently. The xfsl tool integrated into Xfuzzy 3 allows the tuning of complex fuzzy systems, for instance, hierarchical systems with modules in cascade. The authors propose the use of this tool for tuning a complex fuzzy system for video deinterlacing in this paper. The parameters obtained after tuning are proven by de-interlacing a wide battery of sequences. The use of tuning techniques improves the quality of de-interlacing and provides an algorithm simplification that facilitates its hardware implementatio

A motion and edge adaptive interlaced-to-progressive conversion using fuzzy logic-based systems

This paper presents an algorithm for video de-interlacing. The approach uses three fuzzy logic-based systems to adapt the interpolation strategy to the presence of motion and edges. Furthermore, the algorithm is able to deal with any kind of TV material independently of the source used to acquire the scene. Extensive simulations of standard and real sequences prove the efficiency of the proposed algorithmMinisterio de Educación y Ciencia TEC2005-04359 y DPI2005-02293Junta de Andalucía TIC2006-635 y TEP2006-37

Soft computing techniques for video de-interlacing

This paper presents the application of soft computing techniques to video processing. Specially, the research work has been focused on de-interlacing task. It is necessary whenever the transmission standard uses an interlaced format but the receiver requires a progressive scanning, as happens in consumer displays such as LCDs and plasma. A simple hierarchical solution that combines three simple fuzzy logicbased constituents (interpolators) is presented in this paper. Each interpolator specialized in one of three key image features for de-interlacing: motion, edges, and possible repetition of picture areas. The resulting algorithm offers better results than others with less or similar computational cost. A very interesting result is that our algorithm is competitive with motion-compensated algorithm

Program for deinterlacing in video sequences of different formats

Cílem této diplomové práce je nastudovat současné možnosti využití progresivních algoritmů pro odstranění prokládání ve videosekvencích. První část práce je věnována teorii, základním poznatkům a vlastnostem zpracování s využitím multimediálních dat. Druhá část je věnována zobrazování signálu na různých zobrazovačích při použití prokládaného i progresivního řádkování. Další část je zaměřena na metody konverzí mezi prokládaným řádkováním a progresivním. Poslední část se věnuje implementaci nastudovaných metod. Algoritmus je implementován v jazyce C++, který poskytuje dostatečně rychlé zpracování algoritmů. Závěr práce je věnován otestování a ověření nastudovaných algoritmů.The aim of this thesis is a study of advanced algorithms for removing interlacing in digital video sequences. The first part of the work is devoted to the theory, basic knowledge and processing characteristics using multimedia data. The second part is devoted to displaying the signal using interlaced and progressive spacing. The following part is focused on methods of conversion between the interlaced line spacing and progressive spacing. The last part deals with implementation of the proposed methods. The algorithm is implemented in C++ language, which provides sufficiently fast processing algorithms. The conclusion of work is focused in testing and verification of the implemented algorithms.