Adaptive deinterlacing of video sequences using motion data

In this work an efficient motion adaptive deinterlacing method with considerable improvement in picture quality is proposed. A temporal deinterlacing method has a high performance in static images while a spatial method has a better performance in dynamic parts. In the proposed deinterlacing method, a motion adaptive interpolator combines the results of a spatial method and a temporal method based on motion activity level of video sequence. A high performance and low complexity algorithm for motion detection is introduced. This algorithm uses five consecutive interlaced video fields for motion detection. It is able to capture a wide range of motions from slow to fast. The algorithm benefits from a hierarchal structure. It starts with detecting motion in large partitions of a given field. Depending on the detected motion activity level for that partition, the motion detection algorithm might recursively be applied to sub-blocks of the original partition. Two different low pass filters are used during the motion detection to increase the algorithm accuracy. The result of motion detection is then used in the proposed motion adaptive interpolator. The performance of the proposed deinterlacing algorithm is compared to previous methods in the literature. Experimenting with several standard video sequences, the method proposed in this work shows excellent results for motion detection and deinterlacing performance

Fuzzy motion adaptive algorithm for video de-interlacing

A motion adaptive algorithm for video de-interlacing is presented in this paper. It is based on a fuzzy inference system, which performs an interpolation between two linear techniques as a function of the motion level. Fuzzy systems with different number of ¿if-then¿ rules have been analyzed and compared in terms of complexity as well as efficiency in de-interlacing benchmark video sequences.Ministerio de Educación y Ciencia TEC2005-04359/MICJunta de Andalucía TIC2006-63

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

HDTV transmission format conversion and migration path

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (leaves 77-79).by Lon E. Sunshine.Ph.D

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

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)

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