Most sensors used for remote sensing (RS) purposes capture more than one component to seize different features from the Earth's surface. Usually, either multispectral images acquired for RS applications are corrected or the user/application determines valid regions within the image. Consequently, regions without information may emerge ( no-data regions). This letter proposes to encode multispectral images with no-data regions through the JPEG2000 framework, taking into account the lack of importance of these irrelevant regions. Experimental results, performed on data from real scenarios, suggest that the best approach analyzed is the shape-adaptive (SA) Karhunen-Loe¿ve transform to decorrelate the spectral redundancy and then the SA multicomponent JPEG2000. The coding-performance improvement over other coding systems considered (Binary Set Splitting with K-D Trees, SA Wavelet Difference Reduction, and SA TARP) is from 5 to 20 dB in signal-to-noise ratio energy.