HiRes deconvolution of Spitzer infrared images

Spitzer provides unprecedented sensitivity in the infrared (IR), but the spatial resolution is limited by a relatively small aperture (0.85 m) of the primary mirror. In order to maximize the scientific return it is desirable to use processing techniques which make the optimal use of the spatial information in the observations. We have developed a deconvolution technique for Spitzer images. The algorithm, "HiRes" and its implementation has been discussed by Backus et al. in 2005. Here we present examples of Spitzer IR images from the Infrared Array Camera (IRAC) and MIPS, reprocessed using this technique. Examples of HiRes processing include a variety of objects from point sources to complex extended regions. The examples include comparison of Spitzer deconvolved images with high-resolution Keck and Hubble Space Telescope images. HiRes deconvolution improves the visualization of spatial morphology by enhancing resolution (to sub-arcsecond levels in the IRAC bands) and removing the contaminating sidelobes from bright sources. The results thereby represent a significant improvement over previously-published Spitzer images. The benefits of HiRes include (a) sub-arcsec resolution (~0".6-0".8 for IRAC channels); (b) the ability to detect sources below the diffraction-limited confusion level; (c) the ability to separate blended sources, and thereby provide guidance to point-source extraction procedures; (d) an improved ability to show the spatial morphology of resolved sources. We suggest that it is a useful technique to identify features which are interesting enough for follow-up deeper analysis

Land classification of south-central Iowa from computer enhanced images

The author has identified the following significant results. Enhanced LANDSAT imagery was most useful for land classification purposes, because these images could be photographically printed at large scales such as 1:63,360. The ability to see individual picture elements was no hindrance as long as general image patterns could be discerned. Low cost photographic processing systems for color printings have proved to be effective in the utilization of computer enhanced LANDSAT products for land classification purposes. The initial investment for this type of system was very low, ranging from $100 to$200 beyond a black and white photo lab. The technical expertise can be acquired from reading a color printing and processing manual

Fully-automatic inverse tone mapping algorithm based on dynamic mid-level tone mapping

High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show LDR content on HDR displays, it needs to be up-scaled using a so-called inverse tone mapping algorithm. Several techniques for inverse tone mapping have been proposed in the last years, going from simple approaches based on global and local operators to more advanced algorithms such as neural networks. Some of the drawbacks of existing techniques for inverse tone mapping are the need for human intervention, the high computation time for more advanced algorithms, limited low peak brightness, and the lack of the preservation of the artistic intentions. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping capable of real-time video processing. Our proposed algorithm allows expanding LDR images into HDR images with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using the full-reference objective quality metrics HDR-VDP-2.2 and DRIM, and carrying out a subjective pair-wise comparison experiment. We compared our results with those obtained with the most recent methods found in the literature. Experimental results demonstrate that our proposed method outperforms the current state-of-the-art of simple inverse tone mapping methods and its performance is similar to other more complex and time-consuming advanced techniques