M = int(N / CR)
k1 = int(N / 8)
dictype = 'DCT'
# dictype = 'DFT'
# dictype = None
mestype = 'Gaussian'
seed = 2019
if mestype is 'Gaussian':
Phi = pys.gaussian((M, N), seed=seed, verbose=True)
print("===observation...")
if dictype is 'DCT':
Psi = pys.dctdict(N)
Psi = pys.dctmat(N)
if dictype is 'DFT':
# Psi = pys.dctdict(N)
Psi = pys.dftmat(N)
plt.figure()
plt.subplot(221)
plt.imshow(X)
plt.title('Orignal image signal')
if dictype is not None:
plt.subplot(222)
plt.imshow(np.abs(Psi))
plt.title('Dictionary matrix (' + dictype + ')')
plt.subplot(223)
plt.imshow(np.abs(np.reshape(np.matmul(Psi, X), (N, N))))
CR = 4
N = H
M = int(N / CR)
k1 = int(N / 8)
dictype = 'DCT'
mestype = 'Gaussian'
seed = 2019
if mestype is 'Gaussian':
Phi = pys.gaussian((M, N), seed=seed, verbose=True)
print("===observation...")
if dictype is 'DCT':
D = pys.dctdict(N)
A = np.matmul(Phi, D)
plt.figure()
plt.subplot(221)
plt.imshow(X)
plt.title('Orignal image signal')
plt.subplot(222)
plt.imshow(D)
plt.title('Dictionary matrix (' + dictype + ')')
plt.subplot(223)
plt.imshow(np.reshape(np.matmul(D, X), (N, N)))
plt.title('Sparse Coefficient (' + dictype + ')')
plt.colorbar()
plt.subplot(224)
# -*- coding: utf-8 -*- # @Date : 2017-07-06 10:38:13 # @Author : Yan Liu & Zhi Liu ([email protected]) # @Link : http://iridescent.ink # @Version : $1.0$ # import numpy as np import matplotlib.pyplot as plt import pysparse as pys import scipy.io as sio print("----------DCT-1D------------") N1 = 64 rcsize1 = (int(np.sqrt(N1)), int(np.sqrt(N1))) OD = pys.dctdict(N1) A1 = pys.showdict(OD, rcsize=rcsize1, stride=(0, 0), plot=False) N2 = 256 rcsize2 = (int(np.sqrt(N2)), int(np.sqrt(N2))) OD = pys.dctdict(N2) A2 = pys.showdict(OD, rcsize=rcsize2, stride=(0, 0), plot=False) N3 = 1024 rcsize3 = (int(np.sqrt(N3)), int(np.sqrt(N3))) OD = pys.dctdict(N3) A3 = pys.showdict(OD, rcsize=rcsize3, stride=(0, 0), plot=False) N4 = 4096 rcsize4 = (int(np.sqrt(N4)), int(np.sqrt(N4))) OD = pys.dctdict(N4)