Edited by Jingchao Cao
GuId:
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This is [an example](http://example.com/ "Title") inline link.
##Problem Set 1: Images as Functions
### Questions
#### 1. Input images
* ps1-2-a-1.png:
* ps1-1-a-2.png:
#### 2. Color planes
* ps1-2-a-1.png:
* ps1-2-b-1.png:
* ps1-2-c-1.png:
* I think ps1-2-b-1.png (img1_green) looks more like a monochrome image.
#### 3. Replacement of pixels
* ps1-3-a-1.png:
#### 4. Arithmetic and Geometric operations
* 0 is the min of the pixel values of img1_green, and 255 is the max. 132 is the mean. 69.52 is the standard deviation. First I use the function `flatten()` to change 2D array of img1_green into 1D array. Then I use functions `min()` and `max()`to calculate the min and max pixel values of img1_green. I compute mean pixel values by dividing the sum of every piexl value in flattened img1_green with the length of the array.
Print results:
__0 255 132 69.5151641486__
Code snippets:
img1_green_array = img1_green.flatten()
min_pixel = min(img1_green_array)
max_pixel = max(img1_green_array)
mean_pixel = sum(img1_green_array) / len(img1_green_array)
std = np.std(img1_green_array)
print min_pixel, max_pixel, mean_pixel, std
* ps1-4-b-1.png:
* ps1-4-c-1.png:
* ps1-4-d-1.png:
#### 5. Noise
* ps1-5-a-1.png:
The sigma is 30.
* ps1-5-b-1.png:
* The second one (ps1-5-b-1.png) looks better.
>
####这是一个普通的段落。
这是另一个普通段落。
AT
