Discrete wavelet transform (DWT) of the image
produces multi resolution representation of an image. The multi resolution representation
provides a simple framework for interpreting the image information. The DWT analyses the
signal at multiple resolution. DWT divides the image into high frequency quadrants and low
frequency quadrants. The low frequency quadrant is again split into two more parts of high
and low frequencies and this process is repeated until the signal has been entirely
decomposed.
International Journal of Signal Processing, Image Processing and Pattern Recognition
Vol. 7, No. 6 (2014)
Copyright ⓒ 2014 SERSC 117
The single DWT transformed two dimensional image into four parts: one part is the low
frequency of the original image, the top right contains horizontal details of the image, the one
bottom left contains vertical details of the original image, the bottom right contains high
frequency of the original image. The low frequency coefficients are more robust to embed
watermark because it contains more information of the original image [2]. The reconstruct of
the original image from the decomposed image is performed by IDWT [16].
The digital wavelet transform are scalable in nature. DWT more frequently used in digital
image watermarking because of its excellent spatial localization and multi resolution
techniques. The excellent spatial localization property is very convenient to recognize the
area in the cover image in which the watermark is embedded efficiently.
The DWT is applied on the host image to decompose the image into four non overlapping