2. [Vector Quantization] Please consider the 4 pixel by 4 pixel image below: 202,118,148 237,141,151 250,172,164 239,166,169 122,36,41 175,53,18 228,43,118 233, 134,60 70,49,62 86,49,35 150,39,43 169,56,58 151,132, 233 169,135,244 179,135,244 174,139,244 The table contains the RGB values of the sixteen pixels. All RGB values are in 8-bit, i.e. from 0 to 255. We intend to quantize the image into 4 levels of color via K-means clustering. a) Assuming we have initial quantization levels of (70,70,70), (120,120,120), (155,155,155), (255,255,255) and use Euclidean distance as a measurement of error calculate the result of the first step of the K-means clustering operation. This includes which quantization level each of the pixels will be quantized to, and what the modified quantization vector would be after the first adjustment. 2. [Vector Quantization] Please consider the 4 pixel by 4 pixel image below: 202,118,148 237,141,151 250,172,164 239,166,169 122,36,41 175,53,18 228,43,118 233, 134,60 70,49,62 86,49,35 150,39,43 169,56,58 151,132, 233 169,135,244 179,135,244 174,139,244 The table contains the RGB values of the sixteen pixels. All RGB values are in 8-bit, i.e. from 0 to 255. We intend to quantize the image into 4 levels of color via K-means clustering. a) Assuming we have initial quantization levels of (70,70,70), (120,120,120), (155,155,155), (255,255,255) and use Euclidean distance as a measurement of error calculate the result of the first step of the K-means clustering operation. This includes which quantization level each of the pixels will be quantized to, and what the modified quantization vector would be after the first adjustment