Preservation of spectral information and the enhancement of spatial resolution are regarded as very important in satellite
image fusion. In previous research, many algorithms simultaneously unsolved these problems, or needed experimental
parameters to enhance fusion performance. This paper proposed a new fusion method based on fast intensity-huesaturation
(FIHS) to merge a high-resolution panchromatic image with a low-resolution multispectral image. It is conducted by multiple regressions for generating synthetic image and statistical ratio-based image enhancement, which is presented as solving the spectral distortion and conserving the spatial information of the panchromatic image. IKONOS datasets were employed in the evaluation. The results showed that the proposed method was better than the widely used image fusion methods, including the FIHS-based method and the Pan Sharpening module in PCI Geomatica. We compared widely used algorithms with adaptive FIHS image fusion using various fusion quality Indexes such as ERGAS, RASE, correlation, and the Q4 index. The images obtained from the proposed algorithm present higher spectral and spatial quality than the results from using other fusion methods. Therefore, the proposed algorithm is very efficient for high-resolution satellite image fusion with an automatic process.
Anaglyph is the simplest and the most economical method for 3D visualization. However, anaglyph has several drawbacks such as loss of color or visual discomfort, e.g., region merging and the ghosting effect. In particular, the ghosting effect, which is caused by green penetrating to the left eye, brings on a slight headache, dizziness and vertigo. Therefore, ghosting effects have to be reduced to improve the visual quality and make viewing of the anaglyph
comfortable. Since red lightness is increased by penetration by green, the lightness of the red band has to be compensated for. In this paper, a simple deghosting method is proposed using the red lightness difference of the left and right images. We detected a ghosting area with the criterion, which was calculated from the statistics of the difference image, and then the red lightness of the anaglyph was changed to be brighter or darker according to the degree of the difference. The amount of change of red lightness was determined empirically. These adjustments simultaneously reduced the ghosting effect and preserved the color lightness within the non-ghosting area. The proposed deghosting method works well, and the goal of this paper was to detect the ghosting area automatically and to reduce the ghosting.