1. A method of vehicle occupant classification for controlling airbag deployment in a vehicle restraint system comprising the steps of: receiving a first image from a first sensor of a predetermined region of interest occupied by a vehicle occupant by an occupant-classification controller; simultaneously receiving a second image from a second sensor of the predetermined region of interest occupied by the vehicle occupant by the occupant-classification controller; dividing the first and second images into an array of equal sized disparity areas; computing a first texture matrix and a second texture matrix for the respective first and second images; calculating a single disparity-map-estimate from the first texture matrix and the second texture matrix; performing an iterative neighborhood update on the disparity map estimate to achieve a disparity map; applying a smoothing filter to the disparity map to generate a smooth disparity map; applying an average disparity threshold map and an adaptive offset map to the smooth disparity map to achieve a binary map; extracting a refined disparity map from the binary map; inputting the refined disparity map into a neural network classifier of the occupant-classification controller; utilizing the binary map to develop a segmented single image for calculation of a wavelet transform; inputting the wavelet transform into the neural network classifier for computation of an array of class confidences and processing the array of class confidences by a processor of the occupant-classification controller for output of the control signal to the vehicle restraint system; computing a pixel disparity map from each paired pixel of the first and second images; converting the pixel disparity map into another binary map; extracting a stereo differential edge density map from the another binary map; inputting the stereo differential edge density map into the neural network classifier; and outputting a control signal for controlling airbag deployment in the vehicle restraint system.