denoise               package:EBImage               R Documentation

_E_n_h_a_n_c_i_n_g _i_m_a_g_e _a_n_d _i_m_a_g_e _c_o_l_o_r_s

_D_e_s_c_r_i_p_t_i_o_n:

     Functions to enhance image colours.

_U_s_a_g_e:


         denoise(x, r=0, ...)
         mediansmooth(x, r=2, ...)
         despeckle(x, ...)

         sharpen(x, r=0, s=0.5, ...)
         umask(x, r=0, s=0.5, amount=5, t=2, ...)

         blur(x, r=0, s=0.5, ...)
         gblur(x, r=0, s=0.5, ...)

         noise(x, type="gaussian", ...)


_A_r_g_u_m_e_n_t_s:


     '_x' An object of 'Image-class'. 

     '_r' The radius of the pixel neighbourhood to take into account. 
          The 0 value enables automatic radius selection. 

     '_s' The standard deviation of the Laplacian ('sharpen') or
          Gaussian ('umask, blur, gblur'), in pixels. For reasonable
          results of most functions, 'r' must be larger than 's'.  

     '_a_m_o_u_n_t' The percentage of the difference between the original 
          and the blur image that is added back into the original. 

     '_t' The threshold in pixels needed to apply the diffence amount.

     '_t_y_p_e' The type of noise to add. 

     '...' Reserved for future use. 

_V_a_l_u_e:

     A transformed image in an object of 'Image-class'.

_D_e_t_a_i_l_s:

     'despeckle' reduces the speckle noise.

     'mediansmooth' smoothes a noisy image by replacing each pixel
     value by  the median in a set of neighbouring pixels as defined by
     radius.

     'blur, gblur' blur an image. 'blur' differs from Gaussian blur, 
     'gblur', in that it uses a separable kernel which is faster but
     mathematically equivalent to the non-separable kernel (implemented
     in 'ImageMagick').

     'sharpen, umask' sharpen an image. 'umask' uses the unsharp mask
     algorithm. The the image is convolved with a Gaussian operator of
     the given radius and standard deviation, 's'. 

     'noise' adds noise to an image. Supported noise types are: 
     ''uniform', 'gaussian'' (default) ', 'multi', 'impulse', 
     'laplace'' and ''poisson''.

_A_u_t_h_o_r(_s):

     Copyright (c) 2005-2006 Oleg Sklyar : osklyar@ebi.ac.uk

_R_e_f_e_r_e_n_c_e_s:

     _ImageMagick_: <URL: http://www.imagemagick.org>.

_S_e_e _A_l_s_o:

     ' Image-class '

