【文件属性】：
文件名称：图像处理DCT compression, dithering, image interpolation
文件大小：1.05MB
文件格式：PDF
更新时间：2021-09-25 04:02:32
图像处理
CT image compression
(a) Implement the simplified DCT compression process above for n = 2, 4, and 8 and
apply it to the attached image. Show the reconstructed images for these three
different cases. [3 images] Compute the PSNR values of the three reconstructed
images and discuss what the PSNR value means here.
(b) Use the same process in (a) with image transformed to YIQ color model and
show the reconstructed image in RGB space. [3 images] Compute the PSNR
values of the three reconstructed images and discuss what the PSNR value
means here.
Dithering
2. Dithering (30%)
Convert the image cat2_gray.png to binary (black and white) image with different
methods of dithering, show the results, and make some comparison with the results.
(a) Apply noise (random) dithering on the provided image and show the result.
[1 image]
(b) Apply average dithering on the provided image and show the result. [1 image]
(c) Apply error diffusion dithering (Floyd-Steinberg algorithm) on the provided
image and show the result. [1 image]
Image Interpolation
Implement the image interpolation function to upsample an image to four times the
original width and height. Implement the following two different interpolation
methods and show the 4× upsampled images.
(a) Apply nearest-neighbor interpolation on the low resolution image, cat3_LR.png,
and compute the PSNR with the original high resolution image, cat3_HR.png.
[1 image]
(b) Apply bilinear interpolation on the low resolution image and compute the PSNR
with the high resolution image. [1 image]
(c) Apply bicubic interpolation on the low resolution image and compute the PSNR
with the high resolution image. [1 image]