It is referred to as the residual quadtree (RQT) coding which takes a combination of operations: transform, quantization, inverse quantization and inverse transform to determine the optimal TU size in a brute-force fashion [1, 5-7].
However, this "try all and select the best" method adopted by the RQT coding will result in high computational complexity and limit real-time HEVC encoders in applications.
Section 3 describes the proposed fast TU size decision method for the RQT coding in HEVC, which incorporates an adaptive maximum transform depth determination (AMTD) algorithm and a full check skipping--early termination (FCS-ET) algorithm.
Fast Transform Unit Size Decision: The RQT coding in HEVC is applied to improve the coding efficiency, but it demands significant computational overhead [2, 3, 5-8].
Undereducated workers are more likely to be males and hold jobs associated with higher RQT and experience than overeducated workers.
Thus, required education and RQT reveal information about entry-level jobs only for those respondents who were new entrants in the labor market.
By splitting the sample into adequately educated, undereducated, and overeducated workers, some preliminary results become apparent in Table 1: Overeducated workers are younger, have less experience, have less tenure in the current job, and report less RQT than adequately and undereducated workers.
In order to more precisely ascertain the relationship between the job match, education, RQT, and experience, a multivariate analysis is applied.
In this paper, we focus on accelerating the search for the best quadtree structure for CTU and RQT in HEVC intra coding.
2.2 Fast algorithm of deciding the structure of RQT
The author of  makes observations on the impact of maximum inter RQT depth for different CU sizes and sets different fixed depths for sizes of 64x64 and 8x8 TU.