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

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

Adaptive format conversion information as enhancement data for scalable video coding

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (p. 143-145).Scalable coding techniques can be used to efficiently provide multicast video service and involve transmitting a single independently coded base layer and one or more dependently coded enhancement layers. Clients can decode the base layer bitstream and none, some or all of the enhancement layer bitstreams to obtain video quality commensurate with their available resources. In many scalable coding algorithms, residual coding information is the only type of data that is coded in the enhancement layers. However, since the transmitter has access to the original sequence, it can adaptively select different format conversion methods for different regions in an intelligent manner. This adaptive format conversion information can then be transmitted as enhancement data to assist processing at the decoder. The use of adaptive format conversion has not been studied in detail and this thesis examines when and how it can be used for scalable video compression. A new scalable codec is developed in this thesis that can utilize adaptive format conversion information and/or residual coding information as enhancement data. This codec was used in various simulations to investigate different aspects of adaptive format conversion such as the effect of the base layer, a comparison of adaptive format conversion and residual coding, and the use of both adaptive format conversion and residual coding.(cont.) The experimental results show adaptive format conversion can provide video scalability at low enhancement bitrates not possible with residual coding and also assist residual coding at higher enhancement layer bitrates. This thesis also discusses the application of adaptive format conversion to the migration path for digital television. Adaptive format conversion is well-suited to the unique problems of the migration path and can provide initial video scalability as well as assist a future migration path.by Wade K. Wan.Ph.D