Sangseok Park

Graduation Semester and Year




Document Type


Degree Name

Doctor of Philosophy in Electrical Engineering


Electrical Engineering

First Advisor

Kamisetty R Rao


Fine-grain scalability (FGS) based on significant and refinement coding is one of the ways to achieve quality scalability by providing a graceful quality degradation through truncations of the FGS enhancement layer. This approach is useful for video conferencing and telephony on wireless networks, which need to ensure real-time and low-delay conditions since they are subject to serious bit rate fluctuations. The simplification of FGS is proposed to reduce the overall complexity for the Progressive Refinement (PR) slice. The one pass scanning structure is introduced to simplify the coding pass of the FGS layers and the code type method is also proposed to improve the coding efficiency. This system is also compliant to the current Scalable Video Coding (SVC) standard and also provides all types of scalability, such as temporal, spatial, and SNR (Signal-to-Noise Ratio) scalabilities. Bit-Depth Scalability (BDS) needs to be secured to provide so-called backward compatibility since 8 bit current display devices and high bit display devices still work simultaneously in consumer markets for a long time. The implementation of BDS can be obtained by reusing the current SVC amendment to H.264 standard. Scalable video coding which is an extension of H.264/AVC provides efficient methods for merging 8 bits per pixel sequences and higher bits per pixel sequences into one scalable bitstream. Texture redundancy of residuals between two spatial layers is reduced by Inter-Layer Intra prediction and motion information is also considered by introducing Inter Layer Motion Prediction. In this research bit-depth scalability is realized by combining both a global look-up table obtained from an arithmetic average and a scale offset approach for each macroblock based on rate distortion performance.


Electrical and Computer Engineering | Engineering


Degree granted by The University of Texas at Arlington