# Using the Guided Fireworks Algorithm for Local Backlight Dimming
## 1 Introduction  
With the development of display technologies, liquid crystal displays (LCDs) have been successfully applied as display devices in many areas. To obtain good visual performance, it is important to set appropriate screen luminance and luminance contrast [1; 2; 3]. By increasing the luminance contrast, the visual quality can be significantly improved [4]. In a traditional LCD system, the backlight is set to a certain luminance level, and then the liquid crystal (LC) transmittance is controlled to display the image [5]. This backlight mode is simple, but because the backlight luminance is the same behind different regions of an image, the image contrast ratio may be low, which will reduce the visual quality. For example, when the backlight luminance behind an image is high, the dark regions in the image may appear greyish rather than true black, because the backlight with high luminance will leak through the dark pixels (backlight leakage) [6]. On the other hand, power consumption is another factor of concern in a display system. Since the backlight of traditional LCD systems is usually set to a high luminance level, the power consumption of these traditional display systems is large. Recently, a new display technology called local backlight dimming has emerged. A local dimming system consists of an LC panel and a light emitting diode (LED) backlight module. It is different from traditional LCDs in that the backlight module of the local dimming system is composed of LED blocks; each block illuminates a small region of LC panel, and its luminance can be controlled independently. A diagram of a local dimming system is shown in Figure 1.  
According to the local dimming model, the backlight blocks behind different regions can be set to different luminance levels. Therefore, the image contrast ratio can be improved and a higher visual quality can be obtained. For example, the dark regions of the image can be set to a low backlight luminance level, which will reduce backlight leakage and increase the image contrast. Setting some backlight blocks to a low luminance level also effectively reduces the power consumption. In a local dimming system, the displayed image quality and the power consumption are the two elements of greatest concern. To achieve higher image quality or lower power consumption, it is necessary to design suitable local dimming algorithms which can effectively set the backlight luminance. In recent years, some local dimming algorithms [7; 8; 9; 10; 11] have been proposed. Most of these algorithms calculate backlight luminance based on the pixel values of the image (algorithms based on image pixel values are called parameter-based algorithms in this paper). For example, the maximum algorithm and the average algorithm [7] take the maximum pixel value and the average pixel value in the image region illuminated by a backlight block, respectively, as the backlight block's luminance level. The Look-Up Table (LUT) algorithm [8] uses a look-up table to correct the difference between the maximum algorithm and the average algorithm. Based on the look-up table, the luminance level of each block is obtained. [PERSON] et al. [9] proposed a novel backlight dimming algorithm to reduce clipping artifacts by minimizing the increment of backlight luminance. [PERSON] et al. [10] presented two models for computing backlight luminance at a given power consumption. The first model could achieve acceptable quality at a low complexity, while the other model could achieve the best possible power-quality at a higher complexity. In our previous work [12], local dimming was taken as an optimization problem. We focused on reducing the image distortion without increasing the power consumption. Therefore, we used peak signal-to-noise ratio (PSNR) to evaluate the displayed image quality, and took maximizing PSNR as the optimization objective. The local dimming algorithm in our work [12] was designed based on evolutionary computation (EC).