Author(s):  
Robert M. Glaeser

It is well known that a large flux of electrons must pass through a specimen in order to obtain a high resolution image while a smaller particle flux is satisfactory for a low resolution image. The minimum particle flux that is required depends upon the contrast in the image and the signal-to-noise (S/N) ratio at which the data are considered acceptable. For a given S/N associated with statistical fluxtuations, the relationship between contrast and “counting statistics” is s131_eqn1, where C = contrast; r2 is the area of a picture element corresponding to the resolution, r; N is the number of electrons incident per unit area of the specimen; f is the fraction of electrons that contribute to formation of the image, relative to the total number of electrons incident upon the object.


Author(s):  
Fatemeh Makouei ◽  
Babak Mohammadzadeh Asl ◽  
Lasse Thurmann Jorgensen ◽  
Borislav Gueorguiev Tomov ◽  
Matthias Bo Stuart ◽  
...  

2018 ◽  
Vol 37 (7) ◽  
pp. 443-454 ◽  
Author(s):  
J. S. Mueller‐Roemer ◽  
A. Stork

2021 ◽  
Vol 9 (3) ◽  
pp. 1-4
Author(s):  
Harshita Mishra ◽  
Anuradha Misra

In today’s world there is requirement of some techniques or methods that will be helpful for retrieval of the information from the images. Information those are important for finding solution to the problems in the present time are needed. In this review we will study the processing involved in the digitalization of the image. The set or proper array of the pixels that is also called as picture element is known as image. The positioning of these pixels is in matrix which is formed in columns and rows. The image undergoes the process of digitalization by which a digital image is formed. This process of digitalization is called digital image processing of the image (D.I.P). Electronic devices as such computers are used for the processing of the image into digital image. There are various techniques that are used for image segmentation process. In this review we will also try to understand the involvement of data mining for the extraction of the information from the image. The process of the identifying patterns in the large stored data with the help of statistic and mathematical algorithms is data mining. The pixel wise classification of the image segmentation uses data mining technique.


2007 ◽  
Vol 45 (2) ◽  
pp. 746-769 ◽  
Author(s):  
Bernhard Beckermann ◽  
Stefano Serra‐Capizzano

1974 ◽  
Vol 100 (7) ◽  
pp. 1459-1472
Author(s):  
William S. Doyle ◽  
Robert L. Harrison
Keyword(s):  

Author(s):  
Lloyd Humberstone

The first philosophically-motivated use of many-valued truth tables arose with Jan Łukasiewicz in the 1920s. What exercised Łukasiewicz was a worry that the principle of bivalence, ‘every statement is either true or false’, involves an undesirable commitment to fatalism. Should not statements about the future whose eventual truth or falsity depends on the actions of free agents be given some third status – ‘indeterminate’, say – as opposed to being (now) regarded as determinately true or determinately false? To implement this idea in the context of the language of sentential logic (with conjunction, disjunction, implication and negation), we need to show – if the usual style of treatment of such connectives in a bivalent setting is to be followed – how the status of a compound formula is determined by the status of its components. Łukasiewicz’s decision as to how the appropriate three-valued truth-functions should look is recorded in truth tables in which (determinate) truth and falsity are represented by ‘1’ and ‘3’ respectively, with ‘2’ for indeterminacy (see tables in the main body of the entry). Consider the formula A∨B (‘A or B’), for example, when A has the value 2 and B has the value 1. The value of A∨B is 1, reasonably enough, since if A’s eventual truth or falsity depends on how people freely act, but B is determinately true already, then A∨B is already true independently of such free action. There are no constraints as to which values may be assigned to propositional variables. The law of excluded middle is invalidated in the case of indeterminacy: if p is assigned the value 2, then p∨ ¬p also has the value 2. This reflects Łukasiewicz’s idea that such disjunctions as ‘Either I shall die in a plane crash on January 1, 2030 or I shall not die in a plane crash on January 1, 2030’ should not be counted as logical truths, on pain of incurring the fatalistic commitments already alluded to. Together with the choice of designated elements (which play the role in determining validity played by truth in the bivalent setting), Łukasiewicz’s tables constitute a (logical) matrix. An alternative three-element matrix, the 1-Kleene matrix, involves putting 2→2=2, leaving everything else unchanged. And a third such matrix, the 1,2-Kleene matrix, differs from this in taking as designated the set of values {1,2} rather than {1}. The 1-Kleene matrix has been proposed for the semantics of vagueness. In the case of a sentence applying a vague predicate, such as ‘young’, to an individual, the idea is that if the individual is a borderline case of the predicate (not definitely young, and not definitely not young, to use our example) then the value 2 is appropriate, while 1 and 3 are reserved for definite truths and falsehoods, respectively. Łukasiewicz also explored, as a technical curiosity, n-valued tables constructed on the same model, for higher values of n, as well as certain infinitely many-valued tables. Variations on this theme have included acknowledging as many values as there are real numbers, with similar applications to vagueness and approximation in mind.


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