KEYWORDS: Image fusion, Wavelets, Image quality, Micro unmanned aerial vehicles, Digital imaging, Information operations, Image compression, Visibility, Human vision and color perception, Digital image processing
When digital images are mosaicked, brightness difference between to-be-mosaicked images will result in mosaic artifacts
in the final mosaicked image due to non-uniformity caused by optical system vignetting as well as gain changes
automatically caused by scene changes. An brightness adaptive algorithm for image mosaic seamless fusion has been
studied in this paper. The process of the method are as follows; 1) estimating the visibility of stitching traces according to
brightness differences between to-be-mosaicked images; 2) adjusting the brightness of the images to be mosaicked in
order to reduce the brightness difference until the mosaic aitifacts can not be perceived by human visual
system; 3)blending the images to be mosaicked based on mul-tiscale analysis method. The experiment indicates that the
method is adaptive to adjust brightness for seamless blending based on multi-scale analysis, and the mosaiced image
quality can meet the requirements of human vision.
The difference of illumination between to-be-mosaicked images will cause mosaic artifacts when digital images are
mosaicked. An objective assessment method of digital images mosaic artifacts visibility based on human visual
perception has been studied in this paper. The process of the method are as follows; 1) the gradient errors image is
obtained according to the to-be-mosaicked images, 2) the just noticeable difference (JND) of reference image is
derived by considering the human visual frequency sensitivity, the brightness mask effects and texture mask effects on
visual resolution comprehensively; 3) the mosaic artifacts image which is perceptible visually can be acquired by
subtracting the JND threshold values from the wavelet coefficients of gradient errors image in wavelet domain. The
mosaic artifacts visibility (MAV) of digital image is constructed to use as an objective assessment index of image
stitching seam visibility by considering the average value and information entropy of the mosaic artifacts image
comprehensively. The experiment indicates that the objective assessment results of digital image mosaic artifacts
visibility by MAV index are consistent with those of the subjective perceptual method basically.
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