DuongHoangThuy

import sys, os, time, numpy, Image, pywt
import matplotlib.pyplot as plt

def wavelet_transform(data, threshold):
    wavelet_type = 'haar'
    clean_coef = list()
    compose = list()

    cA2, cD2, cD1 = pywt.wavedec2(data, wavelet_type, level=2)
    clean_coef.append(cA2)

DuongHoangThuy

from numpy import *
import scipy
import pywt
import sys
import Image
import scipy.ndimage

noiseSigma = 5.0

def denoise(data,wavelet,noiseSigma):

DuongHoangThuy

from PIL import Image
import pywt
import numpy as np

import matplotlib.pyplot as plt
import os

def filtroGrisesPromedio(imagen):
	x, y = imagen.size
	px = imagen.load()

DuongHoangThuy

import math
import sys

'''
python haar.py
python haar.py 1 5 3 1

'''

def wrap(value, ubound):

DuongHoangThuy

#!/usr/bin/env python2

import numpy as np
import cv2 as cv

def FCD( src, mask ):

	A_THRESH = [ 2, 1 ]

	sobel_x = cv.Sobel( src, cv.CV_32F, 1, 0, ksize = 5 )