def METHOD_NAME(data,max_level=-1):
	'''
	Based on: Skellam Shrinkage: Wavelet-Based Intensity Estimation for Inhomogeneous Poisson data
	Related papers: Fast Haar-Wavelet denoising of multidimensional fluorescence microscopy data
	'''
	mode = "periodic"
	wl = "haar"
	n = data.shape[0]
	J = np.ceil(np.log2(n))
	def identify(approx,detail):
		return detail
	def skellam(approx,detail):
		return SkellamThresh(wavelet_coefs=detail,scaling_coefs=approx)
	if max_level == -1 :
		f = multiscale_function_apply(func=skellam,wavelet_name=wl)
	else:
		f = multiscale_function_apply(func=skellam,wavelet_name=wl,max_level=max_level)
	dwt = f(data)
	return pywt.waverec(dwt,wavelet=wl,mode=mode)