/* *****************************************************************************
 *  Name:     
 *  NetID:    
 *  Precept:  
 *
 *  Partner Name:    N/A
 *  Partner NetID:   N/A
 *  Partner Precept: N/A
 *
 *  Hours to complete assignment (optional):
 *
 **************************************************************************** */

Programming Assignment 7: Seam Carving


/* *****************************************************************************
 *  Describe concisely your algorithm to compute the horizontal and
 *  vertical seam. 
 **************************************************************************** */



/* *****************************************************************************
 *  Describe what makes an image ideal for the seam-carving algorithm.
 *  Describe an image that would not work well.
 **************************************************************************** */



/* *****************************************************************************
 *  Perform computational experiments to estimate the running time to reduce
 *  a W-by-H image by one column (i.e., one call to findVerticalSeam() followed
 *  by one call to removeVerticalSeam()). Use a "doubling" hypothesis, where
 *  you successively increase either W or H by a constant multiplicative
 *  factor (not necessarily 2).
 *
 *  To do so, fill in the two tables below. Each table must have 5-10
 *  data points, ranging in time from around 0.25 seconds for the smallest
 *  data point to around 30 seconds for the largest one.
 **************************************************************************** */

(keep W constant)
W = 1000

 H           Column removal time (seconds)
------------------------------------------
...
...
...
...
...


(keep H constant)
H = 1000

 W           Column removal time (seconds)
------------------------------------------
...
...
...
...
...



/* *****************************************************************************
 *  Using the empirical data from the above two tables, give a formula 
 *  (using tilde notation) for the running time (in seconds) as a function
 *  of both W and H, such as
 *
 *       ~ 5.3*10^-8 * W^5.1 * H^1.5
 *
 *  Recall that with tilde notation, you include both the coefficient
 *  and exponents of the leading term (but not lower-order terms).
 *  Round each coefficient and exponent to two significant digits.
 **************************************************************************** */


Running time (in seconds) to remove one column as a function of both W and H:


    ~ 
       _______________________________________




/* *****************************************************************************
 *  Known bugs / limitations.
 **************************************************************************** */


/* *****************************************************************************
 *  Describe whatever help (if any) that you received.
 *  Don't include readings, lectures, and precepts, but do
 *  include any help from people (including course staff, lab TAs,
 *  classmates, and friends) and attribute them by name.
 **************************************************************************** */


/* *****************************************************************************
 *  Describe any serious problems you encountered.                    
 **************************************************************************** */


/* *****************************************************************************
 *  If you worked with a partner, assert below that you followed
 *  the protocol as described on the assignment page. Give one
 *  sentence explaining what each of you contributed.
 **************************************************************************** */


/* *****************************************************************************
 *  List any other comments here. Feel free to provide any feedback   
 *  on how much you learned from doing the assignment, and whether    
 *  you enjoyed doing it.                                             
 **************************************************************************** */