Stochastic Model-Based Image Segmentation Using Functional Approximation (Special Section of Papers Selected from the 8th Digital Signal Processing Symymposium)

スポンサーリンク

概要

• 論文の詳細を見る

• An unsupervised segmentation technique is presented that is based on a layered statistical model for both region shapes and the region internal texture signals. While the image partition is modelled as a sample of a Gibbs/Markov random field, the texture inside each image segment is described using functional approximation. The segmentation and the unknown parameters are estimated through iterative optimization of an MAP objective function. The obtained results are subjectively agreeable and well suited for the requirements of region-oriented transform image coding.

• 1994-09-25

著者

• Kaup Andre

  Institute For Communication Engineering Aachen University Of Technology (rwth)

• Aach Til

  Institute for Communication Engineering, Aachen University of Technology (RWTH)

関連論文

• APPLICATION OF 3D MORPHOLOGICAL OPERATIONS IN THE FRAMEWORK OF A COMPUTER-ASSISTED DIAGNOSIS SYSTEM TO CONSTRUCT THORAX MASK AND REMOVE TRACHEA
• Stochastic Model-Based Image Segmentation Using Functional Approximation (Special Section of Papers Selected from the 8th Digital Signal Processing Symymposium)

スポンサーリンク