Image-Processing-Methodologies-in-Java

Code Description for Image Processing Part_A.java

1. Picture tilt(Picture picture)

This method tilts a picture by rotating the picture 30 degrees clockwise.

To rotate a picture by θ radians counterclockwise, it copies the color of each pixel (cols, rows) in the source picture to a target pixel (colt, rowt) whose coordinates (in int) are given by the following formulas:

colt = (int) ( (cols - colc) × cos θ - (rows - rowc) × sin θ + colc )

rowt = (int) ( (cols - colc) × sin θ + (rows - rowc) × cos θ + rowc )

where colc and rowc are the coordinates (in double) of the center of the width-by-height picture, computed by:

colc = 0.5 × (width - 1)

rowc = 0.5 × (height - 1)

Only copy the pixel if the target pixel is in bounds, so as not to change the dimension of the image. Use black for target pixels with no copied color.

2. Picture emboss(Picture picture)

This method adds an emboss style effect to a picture by applying the following kernel.

A kernel filter modifies the pixels in a picture by replacing each pixel with a linear combination of its neighboring pixels and itself. The matrix that characterizes the linear combination is known as the kernel.

Specifically, to apply a kernel filter to a picture, perform the following operation for each RGB components of each pixel p separately:  Align the center of the kernel on pixel p.

 The new component value of pixel p is obtained by multiplying each kernel element with the corresponding component value, and adding the results. After that, combine the results to get the new color.

For example, to apply an emboss kernel filter to the middle Red component value of 50 of a pixel on some part of a picture:

we compute the new value to be

= (-2)10 + (-1)20 + (0)30 + (-1)40 + (1)50 + (1)40 + (0)10 + (1)20 + (2)30 = 90.

We then combine that with the similar computation on the Green and Blue components to obtain the new color of the corresponding pixel.

Note the following important information about the computation:

Periodic boundary conditions. When applying a kernel filter to a pixel near the boundary, some of its neighboring pixels may not exist. In such cases, assume the leftmost column wraps around to the rightmost column, and vice versa; and the top row wraps around to the bottom row, and vice versa. For example:

Rounding. When applying a kernel filter, the resulting RGB components may become fractional if the kernel weights are fractional. Round each RGB component to the nearest integer, with ties rounding up, with Math.round() and then casting to int.
Clamping. When applying a kernel filter, the resulting RGB components may not remain between 0 and 255. If an RGB component of a pixel is less than 0, set it to 0; if is greater than 255, set it to 255.

3. Picture blur(Picture picture)

This method blurs a picture by applying the following kernel (one-ninth in a 9-by-9 diagonal matrix).

This means applying the diagonal matrix, and then dividing the result by 9:

4. Picture edge(Picture picture)

This method performs edge detection of a picture.

First convert the picture into a grayscale picture. You can achieve that by simply calling the static grayScale(picture) method, which is provided as part of the example code, and is similar to the method created in your lab classes.

Picture grayPic = CW3_Example.grayScale(picture);

Next, apply these two kernels to each grayscale component (you only need to do one computation since all three color components of a grayscale picture are the same) of a pixel, the following:

to obtain the value Gx, and the following

to obtain the value Gy.

Finally, convert to int with casting and clamp the value , and then set the color of that pixel to 255 – G.

Code Description for Image Processing Part_B.java

1. Picture positionalTransform(Picture picture)

This method performs an infinite-superimposed Graphics Slices.

The Infinite-superimposed Graphics Slices effect bevel-cuts the original image at a specific angle, then stacks the cut images infinitely with distorted and size-shrinking effect. This effect creates a feeling of suspense, dreaming and mystery, especially in screenshots of suspense movies.

Description of Steps:

Create a new black image;
Define and calculate the radian of angle between the main diagonal and the left edge – “rad1”;
Define the radian of angel between ‘the line between a certain pixel and the upper left corner’ and the left edge – “rad2”;
Determine each pixel’s position using rad1 and rad2;
For pixels outside the cutting area, throw out of the image range;
For pixels inside the cutting area, change location and paste them infinite times with certain formula;
After the location changing, for every pixel inside the image range, Copy them into the new black image;
Return new image;

See the design document for details.

2. Picture colorTransform(Picture picture)

This method performs a Radar-ray Sketch.

The Radar-ray Sketch effect extract the dark parts and adjust them to corresponding green tone, as well as extract the bright parts and adjust them to corresponding black tone. This effect creates a sense of watching through radar.

Description of Steps

Grayscale the image;
Create a new transparent image;
Use nested loops to extract the adjacent nine pixels’ color centered on any pixel in the image, simultaneously discuss every edge pixel using if and else if statement;
Use kernel filter formula to calculate the new RGB components of each pixel according to the colors of the adjacent nine pixels. The key is to set red and blue RGB component at a low rate and green RGB component at a high rate;
Guarantee the new RGB component of each pixel at the range of 0~255;
Copy every pixel into the new image;
Return new image;