Image quality assessment of endoscopic panorama images
Endoscopic panorama images provide a wide field of view and assist in documentation and navigation. Their performance, registration errors, and blending artifacts have been evaluated. However, the similarity between local panorama regions and their input images based on a quality assessment regarding the human visual system (HVS) has not been addressed. Particularly, panorama regions composed by freehand sequences with varying image quality can result in less contrast and illumination. Thus, we develop a new fidelity score for quantitative image quality assessment based on structural similarity maps adopted to the HVS. The measure indicates how much structural information of relevant structures is preserved in the panorama. For evaluation, panoramas are generated from cystoscopic fluorescence videos, and three blending algorithms are evaluated. Our results show that the fidelity scores are consistent with visual assessments, and can be used to assess blending methods for panorama images specific to the given video sequence.