Two special calorimeters are foreseen for the instrumentation of the very forward region of the ILC detector, a luminometer designed to measure the rate of low angle Bhabha scattering events with a precision better than 10 −3 and a low polar angle calorimeter, adjacent to the beam-pipe. The latter will be hit by a large amount of beamstrahlung remnants. The amount and shape of these depositions will allow a fast luminosity estimate and the determination of beam parameters. The sensors of this calorimeter must be radiation hard. Both devices will improve the hermeticity of the detector in the search for new particles. Finely segmented and very compact calorimeters will match the requirements. Due to the high occupancy fast front-end electronics is needed. The design of the calorimeters developed and optimised with Monte Carlo simulations is presented. Sensors and readout electronics ASICs have been designed and prototypes are available. Results on the performance of these major components are summarised.
Grayscale images are fundamental to many image processing applications like data compression, feature extraction, printing and tone mapping. However, some image information is lost when converting from color to grayscale. In this paper, we propose a light-weight and high-speed image decolorization method based on human perception of color temperatures. Chromatic aberration results from differential refraction of light depending on its wavelength. It causes some rays corresponding to cooler colors (like blue, green) to converge before the warmer colors (like red, orange). This phenomena creates a perception of warm colors "advancing" toward the eye, while the cool colors to be "receding" away. In this proposed color to gray conversion model, we implement a weighted blending function to combine red (perceived warm) and blue (perceived cool) channel. Our main contribution is threefold: First, we implement a high-speed color processing method using exact pixel by pixel processing, and we report a 5.7× speed up when compared to other new algorithms. Second, our optimal color conversion method produces luminance in images that are comparable to other state of the art methods which we quantified using the objective metrics (E-score and C2G-SSIM) and subjective user studies (decolorization and tone mapping). Third, we demonstrate that an effective luminance distribution can be achieved using our algorithm by using global and local tone mapping applications.
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