By Peter W. Hawkes
Advances in Imaging and Electron Physics merges long-running serials--Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. This sequence beneficial properties prolonged articles at the physics of electron units (especially semiconductor devices), particle optics at low and high energies, microlithography, photo technological know-how and electronic photograph processing, electromagnetic wave propagation, electron microscopy, and the computing tools utilized in these kinds of domain names. * Contributions from top foreign students and specialists * Discusses sizzling subject components and offers present and destiny examine tendencies * useful reference and consultant for physicists, engineers and mathematicians
Read or Download Advances in Imaging and Electron Physics PDF
Similar extraction & processing books
This publication is a moment version of the person who used to be released by means of John Wiley & Sons in 1988. The author's goal continues to be an identical in this variation, that is to coach uncomplicated facets of, and techniques of resolution for diffusion phenomena via actual examples. The emphasis is on modeling and method.
The foreign Symposium of Acoustical Imaging has been well known because the optimal discussion board for displays of complicated examine ends up in either theoretical and experimental improvement. Held frequently because 1968, the symposium brings jointly th prime overseas researchers within the region of acoustical imaging.
Laser surprise processing (LSP) is a brand new and promising floor remedy process for bettering the fatigue sturdiness, corrosion, put on resistance and different mechanical homes of metals and alloys. in the course of LSP, the generated surprise wave can introduce a deep compressive residual rigidity into the fabric, because of its high-pressure (GPa-TPa), ultra-fast (several tens nanoseconds), ultra-high strain-rate and high-energy.
This publication covers numerous metallurgical themes, viz. roasting of sulfide minerals, matte smelting, slag, aid of oxides and aid smelting, interfacial phenomena, steelmaking, secondary steelmaking, position of halides in extraction of metals, refining, hydrometallurgy and electrometallurgy. every one bankruptcy is illustrated with applicable examples of functions of the procedure in extraction of a few universal, reactive, infrequent or refractory steel including labored out difficulties explaining the main of the operation
Extra info for Advances in Imaging and Electron Physics
The LMSE (see Eskicioglu and Fisher, 1995), is a local measure for the difference in two images. We compute the following quantities at each pixel (with indices 2 i n À 1 and 2 j m À 1) of X and Y, respectively: Gamut Mapping 23 Lðxij Þ ¼ xðiþ1Þj þ xðiÀ1Þj þ xið jþ1Þ þ xið jÀ1Þ À 4xij and Lðyij Þ ¼ yðiþ1Þj þ yðiÀ1Þj þ yið jþ1Þ þ yið jÀ1Þ À 4yij : The image-quality measure QLMSE is then defined as QLMSE ðX; YÞ ¼ nÀ1 mÀ1 X X 1 ðLðxij Þ À Lðyij ÞÞ2 : ðn À 2Þðm À 2Þ i¼2 j¼2 Another measure considering a local contrast in images is DLC.
Another iterative approach has been proposed by McCann (2001), who describes an iterative gamut-mapping technique based on spatial image compression. The objective in McCann’s approach is to optimize ratios of radiances. In both optimization approaches, the main difficulty is defining an appropriate optimization criterion using a perceptual model. Another Gamut Mapping 31 issue is the computational efficiency that makes use of these algorithms difficult in practical applications. So far, optimization approaches respecting spatial features become so high dimensional that the objective function cannot be optimized directly.
In that case, better results can be achieved by using a linear combination of a global and a personalized model. The best weight for the linear combination can be found by testing multiple values and choosing the one with the highest mean hit rate using cross-validation. 6. GAMUT MAPPING AS AN OPTIMIZATION PROBLEM Gamut mapping can be described as a constrained optimization problem. The objective is to find a mapped image that represents an original image as best as possible, that is, we want to minimize the perceived difference of a mapped image and the original image under the constraint of color gamut limitations.