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Motion-Acuity Test for Visual Field Acuity Measurement with Motion-Defined Shapes

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Coding of segmented images using shape-independent basis functions.

A Kaup¹, T Aach

¹Siemens Corporate Technol., Munich. aach@informatik.mu-Luebeck.de

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|February 16, 2008

Summary

This summary is machine-generated.

This study presents a novel method for describing arbitrarily shaped image segments in object-based image coding. The approach uses shape-independent basis functions for efficient texture approximation, ideal for low bit rate image compression.

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Area of Science:

Computer Vision
Image Processing
Digital Signal Processing

Background:

Object-based image coding requires efficient representation of arbitrarily shaped image segments.
Existing methods often couple texture and contour coding, increasing complexity.

Purpose of the Study:

To develop an efficient method for describing arbitrarily shaped image segments in object-based image coding.
To generalize transform image coding principles for arbitrary shapes.
To achieve high energy compactness and suitability for low bit rate coding.

Main Methods:

Generalizing transform image coding principles for arbitrarily shaped segments.
Approximating region texture using 2-D shape-independent basis functions.
Defining basis functions on a circumscribing rectangle for each segment.

Main Results:

The proposed method achieves high energy compactness for texture description.
The approach is well-suited for low bit rate image coding applications.
Texture description is decoupled from contour coding, simplifying the process.

Conclusions:

The developed method offers an efficient and computationally inexpensive solution for object-based image coding.
Decoupling texture and contour coding leads to a more flexible and efficient system.
The technique is particularly beneficial for achieving low bit rates in image compression.