Representing images using points on image surfaces

• Published in: IEEE transactions on image processing Vol. 14; no. 8; pp. 1043 - 1056
• Main Authors: WANG, Sheng-Jyh, KUO, Lun-Chia, JONG, Hsin-Haw, WU, Zong-Han
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2005; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Artificial Intelligence; B-spline approximation; Data mining; Detection, estimation, filtering, equalization, prediction; differential geometry; Discrete cosine transforms; Discrete Fourier transforms; edge detection; Exact sciences and technology; Image coding; image compression; Image edge detection; image editing; Image enhancement; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image processing; Image reconstruction; Image representation; image surface; Imaging, Three-Dimensional - methods; Information Storage and Retrieval - methods; Information, signal and communications theory; Interpolation; Pattern recognition; Pattern Recognition, Automated - methods; Pixel; Signal and communications theory; Signal processing; Signal Processing, Computer-Assisted; Signal representation. Spectral analysis; Signal, noise; Telecommunications and information theory; B spline; image editing; Linear interpolation; Image processing; Data compression; Differential geometry; Iterative method; Image compression; Signal representation; B-spline approximation; image surface; Shape detection; Image reconstruction; Spline approximation; Image quality; Image coding; Multiscale method; Image representation; Signal processing; Feature extraction; Edge enhancement; Image sensor; Edge detection; Image enhancement
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2005.851693

This paper presents a new approach to represent an image by "verge points," which are defined as high-curvature points on the image surface. This representation offers a compact and reversible way to preserve the essence of the original image. Various applications, such as compression, edge detection, image enhancement, and image editing, can be achieved based on this representation. In this paper, the whole procedure for verge point representation is presented. Based on these verge points, image reconstruction can be easily achieved via iterative linear interpolation. These extracted verge points with compatible properties are further linked into verge curves to offer more compact representation. Progressive representation is also developed based on a multiscale extraction scheme. Some potential applications are then presented to demonstrate the versatility of this representation.