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Spectral index method was widely applied to the inversion of crop chlorophyll content. In the present study, PSR3500 spectrometer and SPAD-502 chlorophyll fluorometer were used to acquire the spectrum and relative chlorophyll content (SPAD value) of winter wheat leaves on May 2nd 2013 when it was at the jointing stage of winter wheat. Then the measured spectra were resampled to simulate TM multispectral data and Hyperion hyperspectral data respectively, using the Gaussian spectral response function. We chose four typical spectral indices including normalized difference vegetation index (NDVD, triangle vegetation index (TVI), the ratio of modified transformed chlorophyll absorption ratio index (MCARI) to optimized soil adjusted vegetation index (OSAVI) (MCARI/OSAVI) and vegetation index based on universal pattern decomposition (VIUPD), which were constructed with the feature bands sensitive to the vegetation chlorophyll. After calculating these spectral indices based on the resampling TM and Hyperion data, the regression equation between spectral indices and chlorophyll content was established. For TM, the result indicates that VIUPD has the best correlation with chlorophyll (R2 = 0.819 7) followed by NDVI (R2 = 0.791 8), while MCARI/OSAVI and TVI also show a good correlation with R2 higher than 0.5. For the simulated Hyperion data, VIUPD again ranks first with R2 = 0.817 1, followed by MCARI/OSAVI (R2 = 0.658 6), while NDVI and TVI show very low values with R2 less than 0.2. It was demonstrated that VIUPD has the best accuracy and stability to estimate chlorophyll of winter wheat whether using simulated TM data or Hyperion data, which reaffirms that VIUPD is comparatively sensor independent. The chlorophyll estimation accuracy and stability of MCARI/OSAVI also works well, partly because OSAVI could reduce the influence of backgrounds. Two broadband spectral indices NDVI and TVI are weak for the chlorophyll estimation of simulated Hyperion data mainly because of their dependence on few bands and the strong influence of atmosphere, solar altitude, viewing angle of sensor, background and so on. In conclusion, the stability and consistency of chlorophyll estimation is equally important to the estimation accuracy by spectral index method. VIUPD introduced in the study has the best performance to estimate winter wheat chlorophyll, which illustrates its potential ability in the area of estimating vegetation biochemical parameters.