Non Local Means

The following documentation has been extracted automatically from the comments found in the source code. Discard Parameters. object variable.

class Parameters_module.Parameters

The input variables are read from the input file. The input file is written with python syntax. The Input file is interpreted as python after a preprocessing The preprocessing was introduced at the time of HST-> PYHST transition to maintaing compatibility with:

• NO/YES meaning 0/1

• items containing FILE in their name can be initialized without using the “” which are otherwise necessary for strings

The input file has to set (some of) the following variables. To setup easily an input file you are suggested to start from one of the examples given in the doc.

BETA_TV = 1.0

• When DENOISING_TYPE=1, the beta entering in the below formula :

\[\frac{1}{2} \left\| Sino - P \cdot Slice \right\|_2^2 + \beta \, TV(Slice)\]

whose value is minimized by the iterative procedure

• When DENOISING_TYPE=4, the beta of the paper http://arxiv.org/abs/1305.1256

DENOISING_TYPE = 1

The kind of denoising used at each step of iterative correction :

• DENOISING_TYPE=1 -> TV denoising (translated to gpu from Emmanuelle Gouillart https://github.com/emmanuelle/tomo-tv/)

  • related parameters : ITERATIVE_CORRECTIONS, DO_PRECONDITION=1, BETA_TV, N_ITERS_DENOISING, DUAL_GAP_STOP,

• DENOISING_TYPE=4 -> Dictionary patching with Overlapping Patches using FISTA + L1 norm. Following http://arxiv.org/abs/1305.1256

  • related parameters : ITERATIVE_CORRECTIONS, BETA_TV, WEIGHT_OVERLAP, PATCHES_FILE, STEPFORPATCHES

• DENOISING_TYPE=5 and ITERATIVE_CORRECTIONS>0 -> NN-FBP: Reconstruct using a trained NN-FBP network

  • related parameters : NNFBP_FILTERS_FILE, NNFBP_NLINEAR

• DENOISING_TYPE=6 and ITERATIVE_CORRECTIONS>0 -> NN-FBP: Create a training set to train a NN-FBP network

  • related parameters : NNFBP_TRAINING_PIXELS_PER_SLICE, NNFBP_TRAINING_RECONSTRUCTION_FILE, NNFBP_NLINEAR,NNFBP_FILTERS_FILE , NNFBP_TRAINING_USEMASK, NNFBP_TRAINING_MASK_FILE , NNFBP_NHIDDEN_NODES

• DENOISING_TYPE=8 -> Wavelet regularization

  • related parameters : W_WNAME, W_LEVELS, W_FISTA_PARAM, W_CYCLE_SPIN, W_SWT

ITERATIVE_CORRECTIONS = 0

The number of iterative correction loops. If zero no iterative correction (default).