Abstract
This paper reviews the implementation of fractal based image interpolation, the associated visual artifacts of the interpolated images, and various techniques, including novel contributions, that alleviate these awkward visual artifacts to achieve visually pleasant interpolated image. The fractal interpolation methods considered in this paper are based on the plain Iterative Function System (IFS) in spatial domain without additional transformation, where we believe that the benefits of additional transformation can be added onto the presented study without complication. Simulation results are presented to demonstrate the discussed techniques, together with the pros and cons of each techniques. Finally, a novel spatial domain interleave layer has been proposed to add to the IFS image system for improving the performance of the system from image zooming to interpolation with the preservation of the pixel intensity from the original low resolution image.
Highlights
The Fractal Image Interpolation refers to image interpolation that makes use of the Partitioned FractalImage (PFI) representation based on an Iterative Function System (IFS)
Within the IFS framework, images are modeled as deterministic fractal objects approximated by different parts of the same image, which is a direct result of the image being self-similar
This paper has shown that fractal image interpolation has the potential to generate high quality interpolated images
Summary
Image (PFI) representation based on an Iterative Function System (IFS). When PFI representation is first introduced in the 1980s, there was a great deal of hope and excitement over the application of fractals to compress natural images, and fractals have spurred a considerable amount of research activities in that period of time. In the IFS framework, the fractal objects are described with a simple recursion, such that images with different sizes (scales) can be generated from the associated fractal codes using the same recursion This property makes changing image resolutions in PFI very easy [1]. Depth map interpolation in 3D computer graphic [10], etc Disregarding their very different applications, the core of these algorithms are the basic PFI, which will be discussed in later sections in this paper. It is the purpose of this paper to review fractal image interpolation from the basics of IFS and to present the mathematical analysis on various techniques that have been presented in literature to alleviate various shortcomings of the fractal image interpolation.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
