Computer Vision, Graphics, and Image Processing
A Multiscanning Approach Based on Morphological Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
A hierarchical morphological image decomposition
Pattern Recognition Letters
A study of the generalized morphological filter
Circuits, Systems, and Signal Processing - Special issue: median and morphological filters
Computing occluding and transparent motions
International Journal of Computer Vision
Performance of optical flow techniques
International Journal of Computer Vision
Computing Optical Flow with Physical Models of Brightness Variation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An edge preserving noise smoothing technique using multiscale morphology
Signal Processing
AI '97 Proceedings of the 10th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
Design considerations for a computer-vision-enabled ophthalmic augmented reality environment
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Towards a Better Comprehension of Similarity Measures Used in Medical Image Registration
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
Image Enhancement by Morphological Pyramid Decomposition and Modified Reconstruction
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
Automatic retinal image registration scheme using global optimization techniques
IEEE Transactions on Information Technology in Biomedicine
A new algorithm for image noise reduction using mathematical morphology
IEEE Transactions on Image Processing
Retinal fundus image registration via vascular structure graph matching
Journal of Biomedical Imaging
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The present paper describes a new and efficient method for registration of retinal angiogram. The presence of noise, the variations in the background, and the temporal variation of fluorescence level poses serious problems in obtaining a robust registration of the retinal image. Here, a multiscale registration scheme is proposed which comprises of three steps. The first step of this work proposes an edge preserving smoothing of the vascular tree. This morphological filtering approach is based on opening and closing with a linear rotating structuring element. For complete preservation of the linear shape of the vascular structures, a morphological reconstruction by dilation of the opened image and a reconstruction by erosion of the closed image are applied. It is proposed to compute the registration transform between two successive original frames, from their morphological gradient. Then, the second step consists in computing the morphological gradient of the two filtered images and radiometrically correcting these gradient images. To take into account the intensity variations, our model incorporates two constant multiplicative and additive factors (based on contrast and brightness) estimated employing a simple analysis of the local histograms (based on a sliding window). In the third step, the proposed method computes the registering transform through a coarse-to-fine (or multiscale) hierarchical approach. After computing the dominant registering transform (which implies the translation) between two successive frames, an elastic transform (also called local affine transform) is carried out to achieve a residual correction. The proposed method is tested by experimental studies, performed on macular fluorescein and Indo cyanine green angiographies. It has been sufficiently demonstrated that our proposed registering method is robust, accurate and fully automated, and it is not based on the extraction of the features or landmarks.