Multi-focus color image fusion in the HSI space using the sum-modified-laplacian and a coarse edge map

Authors:
Hui Zhao;Qi Li;Huajun Feng
Affiliations:
State Key Laboratory of Modern Optical Instrumentation, Department of Optical Engineering, Zhejiang University Hangzhou 310027, PR China;State Key Laboratory of Modern Optical Instrumentation, Department of Optical Engineering, Zhejiang University Hangzhou 310027, PR China;State Key Laboratory of Modern Optical Instrumentation, Department of Optical Engineering, Zhejiang University Hangzhou 310027, PR China
Venue:
Image and Vision Computing
Year:
2008

Citing 10
Cited 4

Object and Texture Classification Using Higher Order Statistics

IEEE Transactions on Pattern Analysis and Machine Intelligence
Accurate Recovery of Three-Dimensional Shape from Image Focus

IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing

Digital Image Processing
Shape from Focus

IEEE Transactions on Pattern Analysis and Machine Intelligence
Multifocus image fusion using artificial neural networks

Pattern Recognition Letters
Analysis and application of autofocusing and three-dimensional shape recovery techniques based on image focus and defocus

Analysis and application of autofocusing and three-dimensional shape recovery techniques based on image focus and defocus
Evaluation of focus measures in multi-focus image fusion

Pattern Recognition Letters
Pattern selective image fusion for multi-focus image reconstruction

CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
Fast algorithms for discrete and continuous wavelet transforms

IEEE Transactions on Information Theory - Part 2
Segmenting a low-depth-of-field image using morphological filters and region merging

IEEE Transactions on Image Processing

3D shape recovery from image focus using kernel regression in eigenspace

Image and Vision Computing
The direct use of curvelets in multifocus fusion

ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Shape from focus using fast discrete curvelet transform

Pattern Recognition
The complex bidimensional empirical mode decomposition

Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presented a simple algorithm for fusion of multi-focus color images. The algorithm was developed in HSI space where the intensity component was not very sensitive to noise. First, an initial decision map was generated by computing the classical SML (sum-modified-laplacian) as the pixels' focus measure using the intensity component; second, by subtracting one of multi-focus images from another, a coarse edge map was obtained to refine the initial decision map; third, a fast region-filling method was used to build the final decision map; fourth, a soft fusion strategy was applied to the transition zone between focused and defocused regions and a nice-looking fused image was generated. Experiments showed that the algorithm was effective and the results were acceptable.