#region  滚动条操作演示 -- 参数传递、亮度与对比度调整       
        static int Lightness = 50;
        static int Contrast_Value = 100;

        static void Main(string[] args)
        {
            Mat src = Cv2.ImRead("lenna.png", ImreadModes.AnyColor);
            if (src.Empty())
            {
                Console.WriteLine("图像未成功加载...");
                return;
            }
            Cv2.ImShow("src image", src);

            TrackbarCallbackNative OnLightness = new TrackbarCallbackNative(Trackbar_Lightness);
            TrackbarCallbackNative OnContrast = new TrackbarCallbackNative(Trackbar_Contrast);

            Cv2.NamedWindow("亮度与对比度调整", WindowFlags.AutoSize);

            System.Runtime.InteropServices.GCHandle handle = System.Runtime.InteropServices.GCHandle.Alloc(src);
            IntPtr ptr = System.Runtime.InteropServices.GCHandle.ToIntPtr(handle);

            Cv2.CreateTrackbar("亮度调整", "亮度与对比度调整", ref Lightness, 100, OnLightness, ptr);
            Cv2.CreateTrackbar("对比度调整", "亮度与对比度调整", ref Contrast_Value, 200, OnContrast, ptr);


            Cv2.WaitKey();
            Cv2.DestroyAllWindows();
        }

        static void Trackbar_Lightness(int pos, IntPtr userData)
        {
            System.Runtime.InteropServices.GCHandle handle = System.Runtime.InteropServices.GCHandle.FromIntPtr(userData);
            Mat src = (Mat)handle.Target;
            Mat Temp_Mat = new Mat(src.Height, src.Width, src.Type(), new Scalar(pos, pos, pos));
            Mat output_Mat = new Mat(src.Height, src.Width, src.Type(), new Scalar(0, 0, 0));


            Cv2.Add(src, Temp_Mat, output_Mat);
            Cv2.ImShow("亮度与对比度调整", output_Mat);
        }

        static void Trackbar_Contrast(int pos, IntPtr userData)
        {
            System.Runtime.InteropServices.GCHandle handle = System.Runtime.InteropServices.GCHandle.FromIntPtr(userData);
            Mat src = (Mat)handle.Target;
            Mat Temp_Mat = new Mat(src.Height, src.Width, src.Type(), new Scalar(0, 0, 0));
            Mat output_Mat = new Mat(src.Height, src.Width, src.Type(), new Scalar(0, 0, 0));
            double Contrast = pos / 100.0;
            Cv2.AddWeighted(src, Contrast, Temp_Mat,0,0, output_Mat);
            Cv2.ImShow("亮度与对比度调整", output_Mat);
        }

cv2.addWeighted()函数说明

        //public static void AddWeighted(InputArray src1, double alpha, InputArray src2, double beta, double gamma, OutputArray dst, int dtype = -1);
        //cv2.addWeighted()函数可以将两张相同shape的图片按权重进行融合，
        //dst = src1* alpha + src2* beta + gamma

        //参数说明：
        //src1 –—— 输入的第一张图片 
        //alpha —— 第一张图片的权重 
        //src2 —— 与第一张大小和通道数相同的图片(相同shape) 
        //beta —— 第二张图片的权重 
        //dst —— 输出，python中可以直接将dst放在前面作为输出
        //gamma —— 加到每个总和上的标量，相当于调亮度 
        //dtype —— 输出阵列的可选深度，默认值为-1.当两个输入数组具有相同深度时，参数为默认值-1.即为src1.depth()。

效果如下：