Why is the colored disparity map only displaying one color?

Question

I have been trying to calculate distances using a frontal parallel stereo setup for a while and I cannot seem to find the reason I get the end-result wrong.

What I did:

• Calibrated both cameras individually using MATLAB's Camera Calibrator

• Calibrated stereo setup while fixing intrinsics

• Loaded image pair from file, used StereoSGBM as well as WLS filter to get the best possible first result for testing

        imgL = cv.imread(path_depth_testing+'/camL3.png')
        imgR = cv.imread(path_depth_testing+'/camR3.png')

        grayL = cv.cvtColor(imgL,cv.COLOR_BGR2GRAY)
        grayR = cv.cvtColor(imgR,cv.COLOR_BGR2GRAY)


        Left_rectified= cv.remap(grayL,Left_Stereo_Map[0],Left_Stereo_Map[1], cv.INTER_LANCZOS4, cv.BORDER_CONSTANT, 0)
        Right_rectified= cv.remap(grayR,Right_Stereo_Map[0],Right_Stereo_Map[1], cv.INTER_LANCZOS4, cv.BORDER_CONSTANT, 0)

        minDisparity = 0
        maxDisparity = 16*25
        numDisparities = maxDisparity-minDisparity
        blockSize = 3
        P1 = 8*3*blockSize**2
        P2 = 32*3*blockSize**2
        disp12MaxDiff = 50
        uniquenessRatio = 15
        speckleWindowSize = 16 
        speckleRange = 64

        left_matcher = cv.StereoSGBM_create(minDisparity = minDisparity,
                numDisparities = numDisparities,
                blockSize = blockSize,
                P1 = P1,
                P2 = P2,
                disp12MaxDiff = disp12MaxDiff,
                uniquenessRatio = uniquenessRatio,
                speckleWindowSize = speckleWindowSize,
                speckleRange = speckleRange,
)

        sigma = 1.5
        lmbda = 8000.0

        right_matcher = cv.ximgproc.createRightMatcher(left_matcher)

        wls_filter = cv.ximgproc.createDisparityWLSFilter(left_matcher)
        wls_filter.setLambda(lmbda)
        wls_filter.setSigmaColor(sigma)

        left_disp = left_matcher.compute(Left_rectified, Right_rectified)
        right_disp = right_matcher.compute(Right_rectified,Left_rectified)
        filtered_disp = wls_filter.filter(left_disp, Left_rectified, 
        disparity_map_right=right_disp)

        temp = filtered_disp.astype(np.float32) / 16
        points_3D = cv.reprojectImageTo3D(temp, Q)

        disp_8 = (filtered_disp/256).astype(np.uint8)
        colored = cv.applyColorMap(disp_8, cv.COLORMAP_JET)
        

• Used mouse callback to extract x, y location from screen and use corresponding X,Y,Z coordinates in depth map

        def printCoordinates(event, x, y, flags, param):
            if event == cv.EVENT_LBUTTONDOWN:
                cv.circle(filtered_disp, (x, y), 50, (0, 255, 255), -1)   
                print('Coordinates on screen x={xscreen}, y={yscreen} [pixels]'.format(xscreen=x, yscreen=y))

                xglobal = points_3D[y][x][0]
                yglobal = points_3D[y][x][1]
                zglobal = points_3D[y][x][2]

        print('Coordinates as seen from left camera x={:.2f}mm, y={:.2f}mm, z={:.2f}mm'.format(xglobal, yglobal , zglobal))

• This is the left camera's image original image

• The resulting disparity map after WLS filter application and the colored version disparity map / colored disparity map

My question is: Why is the colored disparity map in shades of violate instead of the whole JET color range and is there a systematic error in my code that gives me incorrect depths (-50% of the actual depth) to all of the objects?