Application of Biogeography-Based Optimization in Image Processing

Computer image processing gives rise to many optimization problems, which can be very difficult when the images are large and complex. In this chapter, we use BBO and its improved versions to a set of optimization problems in image processing, including image compression, salient object detection, and image segmentation. The results demonstrate the effectiveness of BBO in optimization problems in image processing.

[1]  Y. Fisher.  Fractal image compression with quadtrees , 1995 .

[2]  Yu Xue,et al.  A hybrid biogeography-based optimization and fuzzy C-means algorithm for image segmentation , 2017, Soft Computing.

[3]  Jyh-Horng Jeng,et al.  Fractal image compression using visual-based particle swarm optimization , 2008, Image Vis. Comput..

[4]  Zhicheng Wang,et al.  Salient object detection using biogeography-based optimization to combine features , 2015, Applied Intelligence.

[5]  Wenyin Gong,et al.  DE/BBO: a hybrid differential evolution with biogeography-based optimization for global numerical optimization , 2010, Soft Comput..

[6]  R. K. Agrawal,et al.  A novel approach to combine features for salient object detection using constrained particle swarm optimization , 2014, Pattern Recognit..

[7]  Xiao-Bei Wu,et al.  Hybrid Biogeography-Based Optimization for Integer Programming , 2014, TheScientificWorldJournal.

[8]  Ronen Basri,et al.  Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Maoguo Gong,et al.  Fuzzy C-Means Clustering With Local Information and Kernel Metric for Image Segmentation , 2013, IEEE Transactions on Image Processing.

[10]  Yuval Fisher.  Fractal Image Compression , 1994 .

[11]  Jerry L Prince,et al.  Current methods in medical image segmentation. , 2000, Annual review of biomedical engineering.

[12]  Dan Simon,et al.  Biogeography-Based Optimization , 2022 .

[13]  Sam Z. Sun,et al.  A modified Fuzzy C-Means (FCM) Clustering algorithm and its application on carbonate fluid identification , 2016 .

[14]  Nanning Zheng,et al.  Learning to Detect a Salient Object , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Ali Borji,et al.  What/Where to Look Next? Modeling Top-Down Visual Attention in Complex Interactive Environments , 2014, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[16]  Dan Simon,et al.  Blended biogeography-based optimization for constrained optimization , 2011, Eng. Appl. Artif. Intell..

[17]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[18]  Imran N. Junejo,et al.  Dynamic scene understanding using temporal association rules , 2014, Image Vis. Comput..

[19]  Yu-Jun Zheng,et al.  Localized biogeography-based optimization , 2014, Soft Comput..

[20]  Ricardo J. G. B. Campello,et al.  Evolutionary search for optimal fuzzy c-means clustering , 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

[21]  Benoit B. Mandelbrot,et al.  Fractal Geometry of Nature , 1984 .

[22]  Ming-Sheng Wu,et al.  Spatial correlation genetic algorithm for fractal image compression , 2006 .

[23]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[24]  Arnaud E. Jacquin,et al.  Image coding based on a fractal theory of iterated contractive image transformations , 1992, IEEE Trans. Image Process..

[25]  Wei Zhang,et al.  An Adaptive Computational Model for Salient Object Detection , 2010, IEEE Transactions on Multimedia.

[26]  Laurent Itti,et al.  An Integrated Model of Top-Down and Bottom-Up Attention for Optimizing Detection Speed , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[27]  Jiebo Luo,et al.  iCoseg: Interactive co-segmentation with intelligent scribble guidance , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[28]  Yu-Jun Zheng,et al.  Ecogeography-based optimization: Enhancing biogeography-based optimization with ecogeographic barriers and differentiations , 2014, Comput. Oper. Res..