Refined Weighting Function and Momentum-Directed Genetic search pattern algorithm
First Claim
1. An adaptive method of performing block motion estimation comprising:
- (a) calculating a motion vector related index for a first frame according to a first search pattern;
(b) determining a relationship between the motion vector related index and a predetermined threshold for the first frame; and
(c) selecting a first or a second search pattern algorithms for identifying one or more search blocks in a second frame according to the determined relationship between the motion vector related index and the predetermined threshold for the first frame;
wherein the predetermined threshold is determined by refined weighting functions of the first and the second search pattern algorithms;
wherein the refined weighting functions of the first and the second pattern algorithms are numbers of average search points for the first and the second pattern algorithms searching in the first frame;
wherein block motion estimation is performed adaptively for the second frame.
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Abstract
A weighting function (WF) is previously provided to model the number of search points of a pattern search. However, WF fails to properly describe the behavior of the genetic pattern search algorithms due to some over-simplifications in their models. Therefore, a refined weighting function (RWF) is provided to more accurately describe both genetic and non-genetic pattern searches. Moreover, based on the understanding to RWF, two momentum-directed genetic search algorithms are further provided. These new algorithms check the possible mutations according to their likelihood to the preceding successful mutations and further accelerate the previous genetic pattern searches.
11 Citations
27 Claims
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1. An adaptive method of performing block motion estimation comprising:
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(a) calculating a motion vector related index for a first frame according to a first search pattern; (b) determining a relationship between the motion vector related index and a predetermined threshold for the first frame; and (c) selecting a first or a second search pattern algorithms for identifying one or more search blocks in a second frame according to the determined relationship between the motion vector related index and the predetermined threshold for the first frame; wherein the predetermined threshold is determined by refined weighting functions of the first and the second search pattern algorithms; wherein the refined weighting functions of the first and the second pattern algorithms are numbers of average search points for the first and the second pattern algorithms searching in the first frame; wherein block motion estimation is performed adaptively for the second frame. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A momentum-directed genetic pattern search method of performing block motion estimation for a frame, the method comprising:
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(a) selecting a child point proximate to a parent point according to likelihood of the parent point according to previous successful mutations; (b) comparing block matching cost of the parent point and block matching cost of the child point; and (c) setting either the parent point or the child point as a surviving parent point for a successful mutation according to the compared result of the step (b). - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A momentum-directed genetic rhombus pattern search method of performing block motion estimation for a frame, the method comprising:
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(a) selecting a child point from a perimeter portion of a rhombus centered about a parent point according to likelihood of the parent point according to previous successful mutations; (b) comparing block matching cost of the parent point and block matching cost of the child point; and (c) setting either the parent point or the child point as a surviving parent point for a successful mutation according to the compared result of the step (b). - View Dependent Claims (18, 19, 20)
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21. A momentum-directed genetic hexagonal pattern search method of performing block motion estimation for a frame, the method comprising:
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(a) selecting a child point from a perimeter portion of a hexagon centered about a parent point according to likelihood of the parent point according to previous successful mutations; (b) comparing block matching cost of the parent point and block matching cost of the child point; and (c) setting either the parent point or the child point as a surviving parent point for a successful mutation according to the compared result of the step (b). - View Dependent Claims (22, 23, 24, 25, 26, 27)
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Specification