Impact of Video Parameters on The DCT Coefficient Distribution for H.264-Like Video Coders Nejat Kamaci and Ghassan Al-Regib Georgia Institute of Technology, Atlanta, GA 30332, USA ABSTRACT We examine the impact of various encoding parameters on the distribution of the DCT coefficients for H.264-like video coders. We model the distribution of the frame DCT coefficients using the most common Laplacian and Cauchy distributions. We show that the resolution, the quantization levels and the coding type have significant impact on the accuracy of the Laplacian and Cauchy distribution based models. We also show that the transform kernel (4 × 4 vs 8 × 8) has little impact. Moreover, we show that for the video sources that have little temporal or spatial detail, such as flat regions, the distribution of the frame DCT coefficients resembles a Laplacian distribution. When the video source exhibits more detail, such as texture and edges, the distribution of the frame DCT coefficients resembles a Cauchy distribution. The correlation between the details of the video source to the two probability distributions can be used to further improve the estimation of the distribution of the frame DCT coefficients, by using a classification based approach. Keywords: H.264, DCT modeling 1. INTRODUCTION Compression is a key part of the video processing for which numerous video coding standards have been developed and adopted by the industry 1–3 to date. These standards provide us with the necessary tools to compress and encode video sources to satisfy the needs of the visual information processing and communication applications. From the video communications perspective, the user experience is affected by numerous factors including but not limited to the network conditions, and the user environment characteristics such as the user interface ca- pabilities, and the physical environment. The network conditions affect the amount of data transmitted between the subjects. The user environment conditions might dictate certain requirements such as video resolution and complexity. The physical environment of the environment also affect the quality of the coded video because the output bit rate and the quality of the coded video depends on the statistical characteristics of the video source. To improve the video experience in video communications, the video subsystem can be designed to handle the aforementioned variations in an efficient manner. The encoded video can be adapted based on the conditions of the communication environment, and therefore a good understanding of the impact of the communication environment on the video coding performance is crucial. From the video coding point of view, this translates into how the coded video output will be affected by the nature of the source video and the coding constraints. Most of the video coding algorithms use a block-based spatial transform as part of the coding algorithm. The two-dimensional discrete cosine transform (DCT) is the most common used transform. The statistical properties of the DCT coefficients in a transform-based video coding algorithm has great importance in satisfying the application constraints and controlling the quality of the coded video. In the literature, several studies on the statistical distribution of the transform coefficients have been proposed. The AC coefficients were conjectured to have Gaussian, 4 Laplacian, 5 Cauchy, 6 or more complex distributions. 7 Among these, the Laplacian distribution has been the most popular because of its simplicity. Further author information: (Send correspondence to Prof. Al-Regib) Ghassan Al-Regib : E-mail: alregib@gatech.edu Nejat Kamaci: E-mail: nejat.kamaci@gmail.com