A structural similarity-inspired performance assessment model for multisensor image registration algorithms

Multisensor Image Registration

We describe an approach for registration of images from diierent sensors that may generate local polarity reversals and inconsistent features. The developed technique is based on modifying the objective function by transforming the images into a representation that is less dependent on the local image intensity, and using an iterative process that reduces the eeect of inconsistent features.

Similarity measures for image registration

Multisensor image registration by feature consensus

1 Summary In this paper, we address the problem of registering two images obtained using diierent sensors, elds of view and/or lighting conditions, where conventional approaches relying on feature correspondence or area correlation are likely to fail. The approach presented in this paper eliminates the need for feature matching, and is robust to variations in sensor characteristics, imaging con...

A Novel Image Structural Similarity Index Considering Image Content Detectability Using Maximally Stable Extremal Region Descriptor

The image content detectability and image structure preservation are closely related concepts with undeniable role in image quality assessment. However, the most attention of image quality studies has been paid to image structure evaluation, few of them focused on image content detectability. Examining the image structure was firstly introduced and assessed in Structural SIMilarity (SSIM) measu...

Structural Similarity Based Image Quality Assessment

It is widely believed that the statistical properties of the natural visual environment play a fundamental role in the evolution, development and adaptation of the human visual system (HVS). An important observation about natural image signals is that they are highly structured. By “structured signal”, we mean that the signal samples exhibit strong dependencies amongst themselves, especially wh...