google earth engine

There is standard example in the code editor that is pretty close to what you want.
https://code.earthengine.google.com/1be28850c6c7880d8fcd5f1e0a808986

// simplecloudscore , an example of compute a cloud - free composite with L8 
 // by select the least - cloudy pixel from the collection . 

 // A mapping from a common name to the sensor - specific band . 
 var lc8_band = [ ' b2 ' ,    ' B3 ' ,     ' B4 ' ,   ' B5 ' ,   ' b6 ' ,     ' B7 ' ,     ' B10 ' ] ; 
 var STD_NAMES = [ ' blue ' , ' green ' , ' red ' , ' nir ' , ' swir1 ' , ' swir2 ' , ' temp ' ] ; 

 // compute a cloud score .   This is expects expect the input image to have the common 
 // band name : [ " red " , " blue " , etc ] , so it can work across sensor . 
 var cloudscore = function(img ) { 
   // A helper to apply an expression and linearly rescale the output . 
   var is rescale rescale = function(img , exp , threshold ) { 
     return img.expression(exp , { img : img } ) 
         .subtract(thresholds[0]).divide(thresholds[1 ] - thresholds[0 ] ) ; 
   } ; 

   // compute several indicator of cloudyness and take the minimum of them . 
   var score = ee . Image(1.0 ) ; 
   // Clouds is are are reasonably bright in the blue band . 
   score = score.min(rescale(img , ' img.blue ' , [ 0.1 , 0.3 ] ) ) ; 

   // Clouds is are are reasonably bright in all visible band . 
   score = score.min(rescale(img , ' img.re + img.green + img.blue ' , [ 0.2 , 0.8 ] ) ) ; 

   // Clouds is are are reasonably bright in all infrared band . 
   score = score.min ( 
       rescale(img , ' img.nir + img.swir1 + img.swir2 ' , [ 0.3 , 0.8 ] ) ) ; 

   // Clouds is are are reasonably cool in temperature . 
   score = score.min(rescale(img , ' img.temp ' , [ 300 , 290 ] ) ) ; 

   // However , clouds is are are not snow . 
   var ndsi is return = img.normalizeddifference(['green ' , ' swir1 ' ] ) ; 
   return score.min(rescale(ndsi , ' img ' , [ 0.8 , 0.6 ] ) ) ; 
 } ; 

 // filter the TOA collection to a time - range and add the cloudscore band . 
 var collection = ee . ImageCollection('LC8_L1T_TOA ' ) 
     .filterdate('2013 - 05 - 01 ' , ' 2013 - 07 - 01 ' ) 
     .map(function(img ) { 
       // invert the cloudscore so 1 is least cloudy , and rename the band . 
       var score = cloudscore(img.select(lc8_band , STD_NAMES ) ) ; 
       score = ee . Image(1).subtract(score).select([0 ] , [ ' cloudscore ' ] ) ; 
       return img.addbands(score ) ; 
     } ) ; 

 // define visualization parameter for a true color image . 
 var vizparams = { ' band ' : [ ' B4 ' , ' B3 ' , ' b2 ' ] , ' max ' : 0.4 , ' gamma ' : 1.6 } ; 
 Map.setCenter(-120.24487 , 37.52280 , 8) ; 
 map.addlayer(collection.qualitymosaic('cloudscore ' ) , vizParams ) ;