quantization matrix wip

This commit is contained in:
2024-05-06 01:14:53 +02:00
parent 75dff82f0f
commit dcf4be921c
2 changed files with 77 additions and 3 deletions
+1 -1
View File
@@ -18,7 +18,7 @@ impl Cfg{
fn main() { fn main() {
//Init all descriptors: //Init all descriptors:
let desc = DCT; let desc = DCT::new();
let args: Vec<String> = env::args().collect(); let args: Vec<String> = env::args().collect();
//dbg!(args); //dbg!(args);
+76 -2
View File
@@ -45,14 +45,76 @@ impl Descriptor for Median {
} }
} }
pub struct DCT; /// A struct representing a Discrete Cosine Transform descriptor
/// Transforms an image into an 8x8 grayscale version, and transforms it
/// into the frequency domain
pub struct DCT {
quantization_matrix: [u8; 64],
}
/// Interprets a 64-element array as an 8x8 matrix
/// returns a nicely printable string
fn print_matrix<T: ToString>(array: [T; 64]) -> String {
let mut output = String::new();
for x in 0..8 {
for y in 0..8 {
output.push_str(&array[x*8+y].to_string());
output.push_str(",\t");
}
output.push('\n');
}
output
}
// Define S such that if (Q < 50), then S = 5000/Q, else S = 200 2*Q.
// The output quantization matrix Ts[i,j] at each location of row i and column j is such that
// Ts[i,j] = floor((S * Tb[i,j] + 50) / 100)
impl DCT {
pub fn new() -> DCT {
let base_quantization_matrix: [u8; 64] = [
16, 11, 10, 16, 24, 40, 51, 61,
12, 12, 14, 19, 26, 58, 60, 55,
14, 13, 16, 24, 40, 57, 69, 56,
14, 17, 22, 29, 51, 87, 80, 62,
18, 22, 37, 56, 6, 10, 103, 77,
24, 35, 55, 64, 8, 10, 113, 92,
49, 64, 78, 8, 10, 12, 12, 101,
72, 92, 95, 9, 11, 10, 103, 99,
];
DCT { quantization_matrix: base_quantization_matrix }
}
pub fn quantization_matrix(&self, quality: u8) -> [u8; 64] {
let mut quantization_matrix = self.quantization_matrix.clone();
let scalar: f32 = match quality {
1..=49 => 5000.0/quality as f32,
50..=100 => 200.0 - 2.0*quality as f32,
_ => 1.0 //TODO: error
};
for i in 0..64 {
quantization_matrix[i] = ((scalar * self.quantization_matrix[i] as f32 + 50.0) / 100.0).floor() as u8;
if quantization_matrix[i] == 0 {
quantization_matrix[i] = 1;
}
}
quantization_matrix
}
}
impl Descriptor for DCT { impl Descriptor for DCT {
fn describe(&self, img: image::DynamicImage) -> u64 { fn describe(&self, img: image::DynamicImage) -> u64 {
let quality: u8 = 15;
let qmatrix = self.quantization_matrix(quality);
println!("Base quantization matrix:\n{}", print_matrix(self.quantization_matrix));
println!("Q-{} quantization matrix:\n{}", quality, print_matrix(qmatrix));
let mut dct_values: [f64; 64] = [0.0; 64]; let mut dct_values: [f64; 64] = [0.0; 64];
let mut reconstructed: [u8; 64] = [0; 64]; let mut reconstructed: [u8; 64] = [0; 64];
let img = self.resize(img); let img = self.resize(img);
let _ = img.save("resize.png").expect("Error saving file"); img.save("resize.png").expect("Error saving file");
for u in 0..8 { for u in 0..8 {
for v in 0..8 { for v in 0..8 {
let k = (v*8)+u; let k = (v*8)+u;
@@ -79,6 +141,17 @@ impl Descriptor for DCT {
//println!{"{}", dct_values[k]} //println!{"{}", dct_values[k]}
} }
} }
println!("DCT-coefficients:\n {}", print_matrix(dct_values));
// Quantization:
for i in 0..64 {
dct_values[i] = (dct_values[i] / qmatrix[i] as f64).round();
}
println!("DCT-coefficients, quantized:\n {}", print_matrix(dct_values));
// De-quantization:
for i in 0..64 {
dct_values[i] = dct_values[i] * qmatrix[i] as f64;
}
println!("DCT-coefficients, de-quantized:\n {}", print_matrix(dct_values));
for k in 0..64 { for k in 0..64 {
let x = (k%8) as f64; let x = (k%8) as f64;
let y = (k/8) as f64; let y = (k/8) as f64;
@@ -106,6 +179,7 @@ impl Descriptor for DCT {
//println!("Reconstructed pixel: {}", sum); //println!("Reconstructed pixel: {}", sum);
reconstructed[k] = std::cmp::min(255_u8, sum as u8); reconstructed[k] = std::cmp::min(255_u8, sum as u8);
} }
//println!("{}", print_matrix(reconstructed));
save_buffer( save_buffer(
"reconstructed.png", "reconstructed.png",
&reconstructed, &reconstructed,