A simple transform domain-based low level primitives preserving texture synthesis
by S. Anuvelavan; M. Ganesh; P. Ganesan
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 17, No. 4, 2020

Abstract: In this work, a new patch-based texture synthesis scheme with orthogonal polynomials model coefficients is presented. The proposed scheme has four phases. In the first phase, a block matching technique that identifies a best match, to synthesis in the output image of bigger size is designed in terms of ordered orthogonal polynomials model coefficients. In case of successful match of block, called patch-hit, the proposed scheme finds candidate blocks with triangular search, in the next phase. In the patch selection phase, the proposed scheme considers a subset of orthogonal polynomials model coefficients among the blocks, for the purpose of synthesis which consumes less memory and time. This synthesised output is smoothened in the final phase, by preserving the low level contents between the synthesised patches. The performance of the proposed scheme is measured with energy, contrast, correlation, homogeneity and entropy between the original and synthesised images and is also compared with existing texture synthesis schemes. The results are encouraging.

Online publication date: Fri, 16-Oct-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Intelligence and Data Mining (IJBIDM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com