User Interaction for Image Recolouring using £2

Color Transfer With Salient Features Mapping via Attention Maps Between Images

“…In order to attack the above problems, some local color transfer methods considering the color correspondence and spatial relationship are presented in [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25]. The local color transfer methods are divided into two groups: traditional methods and machine learning methods.…”

“…The latter group includes color style changed with neural network [18], deep learning framework [19], and colorization with the SVM algorithm [20]. These local color transfer methods can also be classified as automatic methods [4,12,[18][19][20][21] and interactive methods [17,[22][23][24][25], where the former ones refer to the automatic local color mapping without manual intervention to region matching, and the latter means the allowance of users in defining the correspondence by sketches or rectangles. Compared with global color transfer methods, local methods usually work better in processing the textures and salient regions of an image.…”

An Adaptive Colour Calibration for Crowdsourced Images in Heritage Preservation Science

“…spectrometers, the analysis of the results must be coherent in a way of being assumed as absolute and unbiased. However, as visual information is perceptual, there exist different approaches for camera homogenisation that evaluate their results employing measures taking perception into account, such as SSIM or the S-CIELAB model (named by some authors Color Image Difference -CID), after performing the needed corrections between samples [21] [34]. Depending on the scientific application either one of the approaches is correct.…”

Advances in colour transfer

“…This strategy is specially adapted when working with GMMs. For instance, Grogan et al [49] (2017) limit the GMM to 50 clusters and normalise all the weights to .…”