LCD Motion Blur Reduction: A Signal Processing Approach

Abstract

Liquid crystal displays (LCDs) have shown great promise in the consumer market for their use as both computer and television displays. Despite their many advantages, the inherent sample-and-hold nature of LCD image formation results in a phenomenon known as motion blur. In this work, we develop a method for motion blur reduction using the Richardson-Lucy deconvolution algorithm in concert with motion vector information from the scene. We further refine our approach by introducing a perceptual significance metric that allows us to weight the amount of processing performed on different regions in the image. In addition, we analyze the role of motion vector errors in the quality of our resulting image. Perceptual tests indicate that our algorithm reduces the amount of perceivable motion blur in LCDs.

Filter banks for improved LCD motion

“…(4) where it is clear that the signal at Àz 0 is set to zero on both sub-bands and therefore cannot be recovered. In order to avoid this complication we will deviate from the ideal motion filter used in [4] and instead allow a non-zero response time, thus pushing the zeros off of the unit circle (Fig. 3).…”

“…As in [4] a soft threshold approach is employed in which the application of the inversion procedure is weighted based on the perceptual significance of the respective region. In many typical images, regions susceptible to motion blur have strong edges and features that lie perpendicular to the direction of motion.…”

“…Each clip was processed either using the FB algorithm described in Section 3 or the RL method [4] to reduce the motion blur caused by global motion. 2 The clips were chosen and cropped such that they did not contain a significant amount of local motion.…”

“…Previous methods for reducing sample-and-hold motion blur can be put into three groups: modification of the display properties, frame rate doubling, and data preprocessing [3,4]. Modifying the display properties by flashing the LCD backlight such that the image is formed more like a CRT [5,6] is effective in reducing motion blur but introduces additional artifacts such as contrast reduction, flickering, and luminance reduction [7].…”

“…Data pre-processing methods such as motion compensated inverse filtering (MCIF) [3] and Richardson-Lucy (RL) based pre-processing [4] pre-process the signal before it is sent to the display using a model for the human visual system. Although the RL method does a good job of pre-processing the signal, its iterative nature make it difficult to implement in a real time hardware system.…”