Self-Validation Pixel Up-Sampling Framework and its Related Algorithm and Architecture Design
Date Issued
2014
Date
2014
Author(s)
Liu, Yi-Nung
Abstract
Pixel interpolation is well known as an ill-posed problem of video restoration.
In this thesis, a self-validation framework is proposed to solve different kinds of
interpolation problems. And corresponding hardware architecture were analysed.
In the proposed self-validation framework, multiple algorithms under differ-
ent assumptions were performed to generate multiple candidate results. After
that, the final estimation of a missing pixel sample was decided adaptively by
evaluating the local consistency of each algorithm with a process called double
interpolation. By combining the results of different algorithms, the color artifacts
are reduced. The proposed framework is applied to three interpolation problems
include CFA demosaick, image up-scaling,and de-interlacing. Experimental re-
sults demonstrate that the proposed framework improves image and video quality
in both subjective and objective assessments.
We also implemented a spatial up-sampling hardware for TV scaler using the
proposed framework. The corresponding hardware architecture design is also
analysed. The proposed tile-based approach can reduce most of bandwidth and
make the design practical on low cost hardware. As a results, a tile-based low cost
super-resolution hardware is implemented on FPGA.
For spatial-temporal interpolation, a real-time hardware-based perception-aware
motion-compensated frame interpolation algorithm is proposed. We conducted an
experiment to find out the limitations of motion blur perception of human visual
system. And these perceptual limits is used to reduce the computational cost
of frame interpolation without affecting visual quality. The experimental results show that the proposed low-cost algorithm maintains the visual quality of the interpolation
results. Finally, to optimize the trade-off between memory bandwidth
and hardware cost, a dedicated hardware architecture design was also proposed.
The major contributions of this thesis are: First, to apply human visual system
knowledge to image processing and provide high visual quality results without
heavy computation. Second, to propose a unified framework for pixel interpolation
problems and provide solid simulation results. Finally, to optimize the tradeoff
between picture quality and hardware cost to derive a compromising solution
for real applications.
Subjects
自我驗證
像素
去交錯
材質
內插
超解析
Type
thesis
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