A method of imaging a biological tissue sample being implemented by a multi-spectral imaging system, the method comprising: - acquiring image data from the biological tissue sample, the image data comprising multi-spectral unprocessed pixels, each multi-spectral pixel having component spectra; - spectral unmixing of the multi-spectral unprocessed pixels by performing: • selecting a first input pixel by generating a histogram of pixel intensity values from the image data and selecting the first input pixel from the most-frequently occurring pixels in the histogram, • spectral unmixing of the selected first input pixel for generating an unmixing result for the first input pixel wherein the first pixel is processed by execution of an unmixing algorithm for separating the component spectra of the first input pixel, • searching for at least a second pixel in the unprocessed pixels, the second pixel meeting a predefined similarity criterion with respect to the first input pixel, the predefined similarity criterion based on computing a dot product between a normalized value of the first input pixel and a normalized value of the second pixel and comparing the dot product with a threshold, and • if the at least second pixel has been identified by searching the unprocessed pixels, reusing the unmixing result obtained for the first input pixel for unmixing the at least one second pixel without execution of the unmixing algorithm, wherein reusing the unmixing result obtained for the first input pixel for unmixing the at least one second pixel comprises multiplying the unmixing result obtained for the normalized value of the first input pixel with a scaling factor of the first pixel with a scaling factor of the second pixel, wherein the respective scaling factors are respective Euclidean norms of the respective pixels; - if the number of remaining unprocessed pixels is greater than a processing threshold, repeating the steps of selecting, spectral unmixing, searching, and reusing for another first input pixel; and - outputting an output image of the biological tissue comprising the unmixed pixels. - acquiring image data from the biological tissue sample, the image data comprising multi-spectral unprocessed pixels, each multi-spectral pixel having component spectra; - spectral unmixing of the multi-spectral unprocessed pixels by performing: • selecting a first input pixel by generating a histogram of pixel intensity values from the image data and selecting the first input pixel from the most-frequently occurring pixels in the histogram, • spectral unmixing of the selected first input pixel for generating an unmixing result for the first input pixel wherein the first pixel is processed by execution of an unmixing algorithm for separating the component spectra of the first input pixel, • searching for at least a second pixel in the unprocessed pixels, the second pixel meeting a predefined similarity criterion with respect to the first input pixel, the predefined similarity criterion based on computing a dot product between a normalized value of the first input pixel and a normalized value of the second pixel and comparing the dot product with a threshold, and • if the at least second pixel has been identified by searching the unprocessed pixels, reusing the unmixing result obtained for the first input pixel for unmixing the at least one second pixel without execution of the unmixing algorithm, wherein reusing the unmixing result obtained for the first input pixel for unmixing the at least one second pixel comprises multiplying the unmixing result obtained for the normalized value of the first input pixel with a scaling factor of the first pixel with a scaling factor of the second pixel, wherein the respective scaling factors are respective Euclidean norms of the respective pixels; • selecting a first input pixel by generating a histogram of pixel intensity values from the image data and selecting the first input pixel from the most-frequently occurring pixels in the histogram, • spectral unmixing of the selected first input pixel for generating an unmixing result for the first input pixel wherein the first pixel is processed by execution of an unmixing algorithm for separating the component spectra of the first input pixel, • searching for at least a second pixel in the unprocessed pixels, the second pixel meeting a predefined similarity criterion with respect to the first input pixel, the predefined similarity criterion based on computing a dot product between a normalized value of the first input pixel and a normalized value of the second pixel and comparing the dot product with a threshold, and • if the at least second pixel has been identified by searching the unprocessed pixels, reusing the unmixing result obtained for the first input pixel for unmixing the at least one second pixel without execution of the unmixing algorithm, wherein reusing the unmixing result obtained for the first input pixel for unmixing the at least one second pixel comprises multiplying the unmixing result obtained for the normalized value of the first input pixel with a scaling factor of the first pixel with a scaling factor of the second pixel, wherein the respective scaling factors are respective Euclidean norms of the respective pixels; - if the number of remaining unprocessed pixels is greater than a processing threshold, repeating the steps of selecting, spectral unmixing, searching, and reusing for another first input pixel; and - outputting an output image of the biological tissue comprising the unmixed pixels.