Limits...
Perspective texture synthesis based on improved energy optimization.

Bashir SM, Ghouri FA - PLoS ONE (2014)

Bottom Line: Using k- means clustering technique to build a search tree to accelerate the search.Hence, we make use of principal component analysis (PCA) technique to reduce dimensions of input vectors.The high quality results prove that our approach is feasible.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Engineering, Institute of Space Technology, Islamabad, Pakistan; Quality Management Directorate General, Pakistan Space and Upper Atmosphere Research Commission (SUPARCO), Karachi, Pakistan.

ABSTRACT
Perspective texture synthesis has great significance in many fields like video editing, scene capturing etc., due to its ability to read and control global feature information. In this paper, we present a novel example-based, specifically energy optimization-based algorithm, to synthesize perspective textures. Energy optimization technique is a pixel-based approach, so it's time-consuming. We improve it from two aspects with the purpose of achieving faster synthesis and high quality. Firstly, we change this pixel-based technique by replacing the pixel computation with a little patch. Secondly, we present a novel technique to accelerate searching nearest neighborhoods in energy optimization. Using k- means clustering technique to build a search tree to accelerate the search. Hence, we make use of principal component analysis (PCA) technique to reduce dimensions of input vectors. The high quality results prove that our approach is feasible. Besides, our proposed algorithm needs shorter time relative to other similar methods.

Show MeSH
Neighborhood number: An example of replacing pixel-based computation with 2*2 patch.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4197031&req=5

pone-0110622-g006: Neighborhood number: An example of replacing pixel-based computation with 2*2 patch.

Mentions: For example, as shown in Figure 6, for textures with 8*8 square pixels neighborhood, every point in a patch has 4*4 = 16 neighborhoods which contain it, so for four points in a patch there are 16*4 = 64 ones. However, when we process it one patch at a time, for four points in a patch there are just 9 neighborhoods needed. So we reduce the number of neighborhoods which entirely contain the patch relative to a single point, and in like manner time can be saved.


Perspective texture synthesis based on improved energy optimization.

Bashir SM, Ghouri FA - PLoS ONE (2014)

Neighborhood number: An example of replacing pixel-based computation with 2*2 patch.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4197031&req=5

pone-0110622-g006: Neighborhood number: An example of replacing pixel-based computation with 2*2 patch.
Mentions: For example, as shown in Figure 6, for textures with 8*8 square pixels neighborhood, every point in a patch has 4*4 = 16 neighborhoods which contain it, so for four points in a patch there are 16*4 = 64 ones. However, when we process it one patch at a time, for four points in a patch there are just 9 neighborhoods needed. So we reduce the number of neighborhoods which entirely contain the patch relative to a single point, and in like manner time can be saved.

Bottom Line: Using k- means clustering technique to build a search tree to accelerate the search.Hence, we make use of principal component analysis (PCA) technique to reduce dimensions of input vectors.The high quality results prove that our approach is feasible.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Engineering, Institute of Space Technology, Islamabad, Pakistan; Quality Management Directorate General, Pakistan Space and Upper Atmosphere Research Commission (SUPARCO), Karachi, Pakistan.

ABSTRACT
Perspective texture synthesis has great significance in many fields like video editing, scene capturing etc., due to its ability to read and control global feature information. In this paper, we present a novel example-based, specifically energy optimization-based algorithm, to synthesize perspective textures. Energy optimization technique is a pixel-based approach, so it's time-consuming. We improve it from two aspects with the purpose of achieving faster synthesis and high quality. Firstly, we change this pixel-based technique by replacing the pixel computation with a little patch. Secondly, we present a novel technique to accelerate searching nearest neighborhoods in energy optimization. Using k- means clustering technique to build a search tree to accelerate the search. Hence, we make use of principal component analysis (PCA) technique to reduce dimensions of input vectors. The high quality results prove that our approach is feasible. Besides, our proposed algorithm needs shorter time relative to other similar methods.

Show MeSH