Question: Please Complete the Edge Detection assignment in MIPS posted below. A code template in MIPS is also posted below for you to use as your
Please Complete the Edge Detection assignment in MIPS posted below. A code template in MIPS is also posted below for you to use as your starting point. Please begin your code where it says "# your code goes here"



Background: Edge detection is a common technique used in many image processing applications to help delineate entities of interest, such as obstacles along a planned path or cell walls in a microscope slide image. One technique for edge detection examines each pixel and compares its intensity with its nearest neighbors (i.e., the four pixels to the North, South, East, and West). It finds maximum and minimum values (MaxI, Minl) of these data and and an output image is created in which each pixel is given the difference between the max and min (Maxi- Minl) as its new intensity value For this assignment, each input 32x32 image is given as an array of 1024 integers, each integer indicating an intensity value. (This array has been previously derived from a color image by taking the average of each pixel's red, green, and blue (RGB) color component intensities.) Pixels on the boundaries of the image must be handled specially to prevent trying to access neighboring pixels that do not exist (i.e., no image wraparound is allowed). For example, if a pixel is on the top edge of the image, it will not have a northern neighbor, so its intensity will only be compared with those of the other three neighbors. Background: Edge detection is a common technique used in many image processing applications to help delineate entities of interest, such as obstacles along a planned path or cell walls in a microscope slide image. One technique for edge detection examines each pixel and compares its intensity with its nearest neighbors (i.e., the four pixels to the North, South, East, and West). It finds maximum and minimum values (MaxI, Minl) of these data and and an output image is created in which each pixel is given the difference between the max and min (Maxi- Minl) as its new intensity value For this assignment, each input 32x32 image is given as an array of 1024 integers, each integer indicating an intensity value. (This array has been previously derived from a color image by taking the average of each pixel's red, green, and blue (RGB) color component intensities.) Pixels on the boundaries of the image must be handled specially to prevent trying to access neighboring pixels that do not exist (i.e., no image wraparound is allowed). For example, if a pixel is on the top edge of the image, it will not have a northern neighbor, so its intensity will only be compared with those of the other three neighbors
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