Purpose: : These studies were carried out to determine the spectral signatures of retinal structures which can be used for analysis and automated diagnosis of retinal disease. Since conventional pathology cannot determine the nature of retinal lesions in–situ, non–invasive methods must be used to quantify retinal pathology. One such a method may be by applying multispectral and hyperspectral methods and automated data analysis. Methods: : Unstained cross–sections of rabbit retinas mounted on glass slides were placed under a microscope and illuminated by white light. A monochromatic CCD camera combined with a liquid crystal tunable filter operating in the visible range was used to record the images at 10 nm intervals between 440 nm (blue) and 720 nm (red). Two methods were used to characterize the spectral signatures of the constituent tissues. The first required manual segmentation and consisted of determining the gray scale values as a function of frequency of the reflected light for the neural retina, the RPE, the choroid, and the sclera. The second used an unsupervised decomposition called non–negative matrix factorization (NMF) for the same four layers. NMF decomposes a multivariate data set into two matrices; a matrix of spectral signatures and their corresponding spatial distribution. Results: : The reflectance spectrum of each of the tissue layers obtained by the manual method formed a characteristic curve (signature) distinct in the frequency range studied and different for each layer. The signatures recovered using NMF have spatial distributions consistent with those obtained with manual segmentation. Both were consistent in recovering four distinct signatures. Conclusions: : Spectral signature characteristic of each of retinal layers investigated appears to be unique by both methods. As such these signatures lend themselves to being a tool for diagnosing retinal lesions that may have a different neural retina, RPE, choroidal, or scleral component.