CWT is based on correlation of wavelets and given signal over a fixed time. For example,  if signal time length is 1&ie and wavelet length is 1sec.. Then CWT provide correlation indices after every 1sec: resulting in 60 indices. Inference 

CWT color             correlation index value 

Dark                          small   (no disturbance in signal) 

Light                           high (disturbance in the signal)

The  output depends on selection of wavelets 

Dear SNV Ganesh,

 Thanks for your valuable comments. 

Hi Saravanan, 

I found that Torrence and Compo (1998) was very helpful when getting my head around wavelets.

http://paos.colorado.edu/research/wavelets/

Regards, Dan.

Thank you Dear Daniel.

Yes, I agree that the above recommendation for the article written by Torrence and Compo (1998) is a helpful article. However, to interpret the scalogram (the 2-D plot of time vs. frequency where the contour of power, the lower of the two plots you showed) one needs to know the shape of the wavelet used to generate the coefficients contoured in the scalogram. For instance, if one used the Morlet wavelet (sinuoidal), then the red zones in the plot would indicate the time and frequency that have sinusoidal components. However, if a different wavelet was used, then the interpretation would be different.

Dr.Matthew,

Thank you for your valuable answer I have used Morlet window to see low to high-frequency periodicity.