Improving Census Transform by High-Pass with Haar Wavelet Transform and Edge Detection

Abstract

One of the common methods for measuring distance is to use a camera and image processing algorithm, such as an eye and brain. Mechanical stereo vision uses two cameras to shoot the same object and analyzes the disparity of the stereo vision. One of the most robust methods to calculate disparity is the well-known census transform, which has the problem of conversion window selection. In this paper, three methods are proposed to improve the performance of the census transform. The first one uses a low-pass band of the wavelet to reduce the computation loading and a high-pass band of the wavelet to modify the disparity. The main idea of the second method is the adaptive size selection of the conversion window by edge information. The third proposed method is to apply the adaptive window size to the previous sparse census transform. In the experiments, two indexes, percentage of bad matching pixels (PoBMP) and root mean squared (RMS), are used to evaluate the performance with the known ground truth data. According to the results, the computation required can be reduced by the multiresolution feature of the wavelet transform. The accuracy is also improved with the modified disparity processing. Compared with previous methods, the number of operation points is reduced by the proposed adaptive window size method.

Identification and Modeling of College Students’ Psychological Stress Indicators for Deep Learning

“…As a signal analysis tool developed in recent years, wavelet transform has its characteristics including orthogonality, direction selectivity, small amount of analysis data, and resolution variability. ese characteristics of wavelet transform make it often used for noise filtering and waveform detection of ECG signals [15,16].…”

The Stereo Communication Method of Artistic Visual Image Based on CAD Platform

“…Texture feature extraction using wavelet transform has been widely used in texture analysis, image compression, and surface defect detection of industrial products. Wavelet transform is often used for signal multiresolution decomposition [12], assuming the signal is g(x); the discrete wavelet decomposition formula is…”

The stereo matching algorithm based on an improved adaptive support window

“…To solve the problem of the traditional Census transform overly relying on the central pixel and to improve the noise resistance, the weighted average grey value of the pixels in the support window is used as the reference value to construct the bit string instead of the grey value of the central pixel [13,14]. To reduce the computational load of Census transform, wavelet transform is used to down-sample the image [15]. Lingyin et al [16], Li et al [17] combine image gradient information with Census transform to improve the matching accuracy.…”