The underwater light field is complex: 4SM is not a "pushbutton" magic black box for dummies The prospective "operator" must definitely grow up into a seasoned "practitioner"  If the imagery is suitable, a knowledgeable and seasoned 4SM practioner shall obtain satisfaction:
 a first order atmospheric correction of the image,
 a thoroughly deglinted image,
 the calibration of spectral operational attenuation coefficient K in m ^{1}
 the water column correction of the shallow areas of the spectral image (~= a lowtide view),
 along with an estimate of the depth in meters at each shallow pixel, which is pretty close to actual depth,
 without the need or use of any field data .
 If the imagery is not suitable, 4SM shall produce an output anyway: garbage in, garbage out.
 If the practioner is not suitable, 4SM shall produce an output anyway.

the deep water radiance Lsw  Unsuitable deep water radiance Lsw values shall result in unacceptable output
 Deglinting: in many cases, it is necessary to remove the "glint" from the imagery to the extent possible
 This also efficiently removes the haze that surrounds dense clouds
 This also efficiently removes the atmospheric adjacency effect where the landmass is bright and poorly vegetated.
 Unfortunately though, this tends to damage radiances of very shallow bottoms
 Hopefully the image, or part of it, is now suitable for shallow water modeling. Alternately , that image must be discarded
 The outcome is a set of spectral deep water radiances Lsw which are applicable to the whole subarea under study

 A set of spectral LsM values : this represents the brightest shallow substrate which exists inside the subarea under study
 A set of spectral La values : this intends to represent the atmospheric path radiance
 Spectral LsM and spectral La values make up a spectral radiometric model of pixels at null depth: Z=0
the Brightest Pixels Line (BPL)  Ratios K i/K j for all pairs of wavebands i and j are estimated: the slope of the linearized BPL is the ratio Ki/Kj
 Their internal consistency as this system of ratios is required and verified: we found that they need to fit Jerlov's optical classification of marine and coastal water types worldwide.

the atmospheric path radiance La  Combined with Lsw, the Soil Line is used to estimate the atmospheric path radiance La
 This achieves for a first order atmospheric correction of the imagery (cf the "dark pixel" assumption)
 this does not correct for the atmospheric adjacency effect, though.

the color of optically deep water Lw  The BOA deep water radiance is then estimated as Lw=LswLa
 This is the color of the optically deep water column, which is also called water volume reflectance.

the twoways spectral effective attenuation coefficients K  The ratio K i/K j for one pair of visible bands i and j, along with Jerlov's data, are used to approximate effective spectral K val
 Spectral K values provide a consistent estimation of the optical properties of the clearest waters that are present inside the subarea under study.
 This last statement means that results obtained for areas that have less clear waters may be erroneous: this shows in the bottom reflectance results.

 4SM operates the simplified radiative transfer equation on each shallow water pixel, through an iteration of inverse modeling steps.
 the spectral waterleaving radiance is then reversemodeled into a spectral shallow "watercolumn corrected" bottom signature that is compatible with the Soils Line assumption.
 this is achieved by increasing the depth Z until spectral LB is deemed acceptable.
 This yields an estimate of both
 the shallow "water column corrected" bottom spectral signature
 the shallow water depth
 Tide correction: as an option, the estimated depth is then corrected for Height of Tide.
 Seatruth: the estimated depth is then multiplied by a final Depth Correcting Factor to be derived from some existing sea truth.

BOTTOM TYPING 4SM then operates a fully supervised bottom typing scheme 
that need to be given appropriate values in order to alleviate the most conspicuous artifacts in the output:  Threshold on inconsistent high radiance (high saturated radiance is bad data)
 Threshold on inconsistent low radiance (low radiance is bad data)
 Threshold on low radiance (bottom contrast LsLsw is too faint)
