10.1 Video processing part 1: introductory exercise  (Page 5/6)

Once our data streams are setup, we can begin processing by first extracting a portion of input data using dstr_get_2D(). This command pulls the data in and we setup a pointer (in_data) to point to this internal memory spot. We also get a pointer to a space where we can write the output data (out_data) when using dstr_put(). Then we call the component function pre_scale() (in pre_scale.c) to operate on the input data and write to the output data space, using these pointers.

The prescaling function will perform the horizontal scaling by averaging every two pixels. This algorithm operates on four pixels at a time. The entire function is iterated within pre_scale_image() 240 times, which results in 240 * 2 rows of data being processed – but only half of that is output.

Upon returning to the wrapper function, pre_scale_image, a new line is extracted; the pointers are updated to show the location of the new lines and the output we had placed in internal memory is then transferred out. This actually happens in the dstr_put() function – thus is serves a dual purpose; to give us a pointer to internal memory which we can write to, and the transferring of its contents to external memory.

Before pre_scale_image() exits, the data streams are closed, and one line is added to the top and bottom of the image to provide context necessary for the next processing steps (The extra two lines - remember?). Also note, it is VERY important to close streams after they have been used. If not done, unusual things such as random crashing and so may occur which are very hard to track down.

Now that the input image has been scaled to a quarter of its initial size, we will proceed with the four image processing algorithms. In img_proc.c, the set_ptr() function is called to set the variable out_ptr to point to the correct quadrant on the 640x480 output image. Then copy_image(), copy_image.c, is called, performing a direct copy of the scaled input image into the lower right quadrant of the output.

Next we will set the out_ptr to point to the upper right quadrant of the output image and call conv3x3_image() in conv3x3_image.c. As with pre_scale_image(), the _image indicates this is only the wrapper function for the ImageLIB (library functions) component, conv3x3(). As before, we must setup our input and output streams. This time, however, data will be read from the external memory (where we have the pre-scaled image) and into internal memory for processing, and then be written to the output image. Iterating over each row, we compute one line of data by calling the component function conv3x3() in conv3x3.c.

In conv3x3(), you will see that we perform a 3x3 block convolution, computing one line of data with the low pass filter mask. Note here that the variables IN1[i], IN2[i], and IN3[i] all grab only one pixel at a time. This is in contrast to the operation of pre_scale() where the variable in_ptr[i]grabbed 4 pixels at a time. This is because in_ptr was of type unsigned int, which implies that it points to four bytes (the size of an unsigned int is 4 bytes) of data at a time. IN1, IN2, and IN3 are all of type unsigned char, which implies they point to a single byte of data. In block convolution, we are computing the value of one pixel by placing weights on a 3x3 block of pixels in the input image and computing the sum. What happens when we are trying to compute the rightmost pixel in a row? The computation is now bogus. That is why the wrapper function copies the last good column of data into the two rightmost columns. You should also note that the component function ensures output pixels will lie between 0 and 255. For the same reason we provided the two extra "copied" lines when performing the prescale.