Quality Analysis

Quant levels = 2

PSNR = 3.8706

SNR = -7.3856

MSE = 137.0327

Distortion (1/psnr) = 0.2584

Quant levels = 4

PSNR = 4.3529

SNR = -6.9033

MSE = 128.9053

Distortion (1/psnr) = 0.2297

Quant levels = 6

PSNR = 5.6940

SNR = -5.5622

MSE = 114.7516

Distortion (1/psnr) = 0.1756

Quant levels = 8

PSNR = 13.3115

SNR = 2.0553

MSE = 7.3324

Distortion (1/psnr) = 0.0751

Quant levels = 10

PSNR =13.3294

SNR = 2.0732

MSE = 6.6789

Distortion (1/psnr) = 0.0750

Quant levels = 12

PSNR =13.3372

SNR = 2.0809

MSE = 6.1603

Distortion (1/psnr) = 0.0750

Quant levels = 14

PSNR = 13.3371

SNR = 2.0809

MSE = 5.7363

Distortion (1/psnr) = 0.0750

Quant levels = 20

PSNR = 13.3301

SNR = 2.0739

MSE = 4.7854

Distortion (1/psnr) = 0.0750

Quant levels = 32

PSNR = 13.3204

SNR = 2.0642

MSE = 4.3597

Distortion (1/psnr) = 0.0751

Quant levels = 128

PSNR = 13.2824

SNR = 2.0262

MSE = 2.7607

Distortion (1/psnr) = 0.0753

image=imread("E:\sem 7\image vvideo coding\project\SLguitarGUY.png");

img=rgb2gray(image);

macrobock_size = 8;

[IMG,y,x]=macroblocks(img,macrobock_size);

qp=511;

s=dct2(img);

s1=dct2(img(1:macrobock_size,1:macrobock_size));

%thresh = multithresh(s1 ,qp);

%valuesMax = [thresh max(s1(:))];

thresh = (1:qp);

valuesMax = [thresh max(s1(:))];

DCT_tf_img = dct_full_image(IMG,macrobock_size,thresh,valuesMax);

%-----------zig zag-------------------------------------------------------

[rvec,cvec] = zigzag(cell2mat(DCT_tf_img(1,1)));

img_One_D_vector = oneMblockVec(DCT_tf_img,macrobock_size,rvec,cvec);

%-------run length code----------------------------------------------------

run_L_coded = run_length_coding(cell2mat(img_One_D_vector));

%--------huffman------------------------------------------------------------

[g,~,intensity_val] = grp2idx(run_L_coded);

Frequency = accumarray(g,1);

[intensity_val Frequency];

proability = Frequency./sum(Frequency);

dict = huffmandict(intensity_val,proability);

code = huffmanenco(run_L_coded,dict);

recov_IMG = decoderesidual(code,dict,rvec,cvec,y,x,macroblock_size);

imshow(uint8(cell2mat(recov_IMG)))

[peaksnr, snr] = psnr(uint8(cell2mat(recov_IMG)),img)

ms = mse(uint8(cell2mat(recov_IMG)), img)

Dis = [1/peaksnr, 1/snr]

% distort = [0.2584 0.2297 0.1756 0.0751 0.0750 0.0750 0.0750 0.0750 0.0751 0.0753];

% quantizationLVL=[2 4 6 8 10 12 14 20 32 128]

% plot(quantizationLVL,distort);

% xlabel("quantization levels"); ylabel("distortion");

% title("distortion vs bitrate");

%Had to change this function to obtain above results

function transformed=dct_full_image(img,macroblock_size,thresh,valuesMax)

%k1 = macroblock row index

%k2 = macroblock column index

%macroblock_size = number of side pixels in a macroblock

for i = 1:size(img,1)

for j = 1:size(img,2)

DCTtransformed=dct2(cell2mat(img(i,j)));

[quant_image,index] = imquantize(DCTtransformed ,thresh,valuesMax);

transformed(i,j)={quant_image};

end

end

end

•When quantizing the residual the data type changes and when reconstructed total different output came. By typecasting the residual in to uint8 I was able to obtain the expected image

•Selection of quantization was not the optimum hence a pixelated output is obtained.

•From the graph we can see that the best point to minimize the distortion and minimize the bitrate is when quantization level is 8.

•Imquant function is limited in matlab to a specific number of levels.

Because imquant is limited I coded a custom function. But then an error occurs saying that huffman encoding library doesn't have that much codes to represent data.

function transformed=dct_full_image(img,macroblock_size,Q)

%k1 = macroblock row index

%k2 = macroblock column index

%macroblock_size = number of side pixels in a macroblock

for i = 1:size(img,1)

for j = 1:size(img,2)

DCTtransformed=dct2(cell2mat(img(i,j)));

uni=unique(reshape(DCTtransformed,1,[]));

Q = rem(Q,size(uni,1));

uni2 = flip(uni);

thresh = [uni(1:floor(Q/2)) uni2(1:floor(Q/2))];

maxval = [thresh max(DCTtransformed(:))];

[quant_image,index] = imquantize(DCTtransformed ,thresh,maxval);

transformed(i,j)={quant_image};

end

end

end