The aim of the lecture is to present several types of integral transforms for functions whose functional values belong to a complete residual lattice, and are 
a natural extensions of lower and upper lattice-valued fuzzy transforms. Integral transforms are defined using Sugeno-integrals and integral kernels in the 
form of binary fuzzy relations. We present some basic properties of the proposed integral transforms, including the linearity property, which is satisfied 
under specific conditions for comonotonic functions. Further, we present a result on the reconstruction of original functions by integral transforms. Finally, 
we show the application of integral transforms to decision making and signal and image processing, especially, noise filtering and compression/decompression.