IMAGE DEPENDENT ENERGY-CONSTRAINED LOCAL BACKLIGHT DIMMING

In this work, we consider and propose two extensions to an optimization-based image dependent backlight dimming algorithm. The first extension introduces error weighting based on human perception of luminance, aiming to improve the perceived image quality; the second extension adds an adjustable term for power consumption to the cost function, allowing flexible power management. Experimental results show that the proposed solution can achieve better results than other algorithms at several power consumption levels.