Soon-Kak Kwon

Adaptive Simplification of Prediction Modes for H.264 Intra-Picture Coding

In an H.264 coding system, an intra prediction method that uses neighbor pixels within the current picture has been adopted for improving coding efficiency. However the large number of intra prediction modes that must be searched significantly increases the number of operations at the encoder. In this paper, we first investigate the usage distribution of intra prediction modes. Then for the focus region of the picture being coded, all of prediction modes are applied. For the other regions, only the important modes are utilized. Important modes are determined from the usage distribution in the previous coded picture; prediction modes that are utilized more than 10% of the time are considered important. From the simulation results, we can verify that the H.264 encoding time may be reduced by approximately 28% for I-picture only and 7% for I, P-pictures without significant loss in the subjective picture quality.

Motion Estimation Method by Using Depth Camera

Motion estimation in video coding greatly affects implementation complexity. In this paper, a reducing method of the complexity in motion estimation is proposed by using both the depth and color cameras. We obtain object information with video sequence from distance information calculated by depth camera, then perform labeling for grouping pixels within similar distances as the same object. Three search regions (background, inside-object, boundary) are determined adaptively for each of motion estimation blocks within current and reference pictures. If a current block is the inside-object region, then motion is searched within the inside-object region of reference picture. Also if a current block is the background region, then motion is searched within the background region of reference picture. From simulation results, we can see that the proposed method compared to the full search method remains the almost same as the motion estimated difference signal and significantly reduces the searching complexity.

Implementation of GPS signal simulation for drone security using Matlab/Simulink

In this paper, a simulation model of digital intermediate frequency (IF) GPS signal is presented. This design is developed based on mathematical model representing the digitized IF GPS signal. In details, C/A code, navigation data and P code, and the noise models are configured some initial settings simultaneously. Simulation results show that the simulated signals share the same properties with real signals (e.g. C/A code correlation properties, and the spread spectrum). The simulated GPS IF signal data can work as input for various signal processing algorithm of GPS receivers, such as acquisition, tracking, carrier-to-noise ratio (C/No) estimation, and GPS spoofing signal generation. Particularly, the simulated GPS signal can conduct scenarios by adjust SNR values of the noise generator during simulation (e.g. signal outages, sudden changes of GPS signal power), which can be used as setup experiments of spoofing/jamming interference to UAVs for drone security applications.

Picture Quality Control Method for Region of Interest by Using Depth Information

If the region of interest (ROI) is set within the picture of image and video and the high quality is provided in ROI compared to Non ROI, then overall subjective picture quality can be increased. ROI extracted by the color camera only increases the calculation complexity and reduces the extraction accuracy. In this paper, we use depth camera to set the ROI and calculate the object distance from camera, then propose a method that the different picture quality is controlled by depending on the distance of an object. That is, we apply a high quantization step size to the far object, but relatively a low quantization step size to the close object, so better picture quality can be provided. Simulation results show that applying the differential quantization step size to the distance of objects by the proposed method can improve the subjective picture quality.