Fusion and registration of THEOS multispectral and panchromatic images

全色胶片 多光谱图像 计算机科学 人工智能 计算机视觉 图像分辨率 图像融合 图像配准 多光谱模式识别 遥感 过程(计算) 融合 分辨率(逻辑) 图像(数学) 地理 哲学 操作系统 语言学
作者
Tanakorn Sritarapipat,Teerasit Kasetkasem,Preesan Rakwatin
出处
期刊:International Journal of Remote Sensing [Informa]
卷期号:35 (13): 5120-5147 被引量:4
标识
DOI:10.1080/01431161.2014.934402
摘要

This article presents a new method for the fusion and registration of THEOS (Thailand Earth Observation Satellite) multispectral and panchromatic images in a single step. In the usual procedure, fusion is an independent process separated from the registration process. However, both image registration and fusion can be formulated as estimation problems. Hence, the registration parameters can be automatically tuned so that both fusion and registration can be optimized simultaneously. Here, we concentrate on the relationship between low-resolution multispectral and high-resolution panchromatic imagery. The proposed technique is based on a statistical framework. It employs the maximum a posteriori (MAP) criterion to jointly solve the fusion and registration problem. Here, the MAP criterion selects the most likely fine resolution multispectral and mapping parameter based on observed coarse resolution multispectral and fine resolution panchromatic images. The Metropolis algorithm was employed as the optimization algorithm to jointly determine the optimum fine resolution multispectral image and mapping parameters. In this work, a closed-form solution that can find the fused multispectral image with correcting registration is also derived. In our experiment, a THEOS multispectral image with high spectral resolution and a THEOS panchromatic image with high spatial resolution are combined to produce a multispectral image with high spectral and spatial resolution. The results of our experiment show that the quality of fused images derived directly from misaligned image pairs without registration error correction can be very poor (blurred and containing few sharp edges). However, with the ability to jointly fuse and register an image pair, the quality of the resulting fused images derived from our proposed algorithm is significantly improved, and, in the simulated cases, the fused images are very similar to the original high resolution multispectral images, regardless of the initial registration errors.

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